Method and device using inter prediction information

ABSTRACT

Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. In video encoding and decoding, inter-prediction information for a target block may be derived, and inter prediction for a target block may be performed using the derived inter-prediction information. Combined inter-prediction information may be performed by combining multiple pieces of inter-prediction information, and the combined inter-prediction information may be added as a candidate to a list used for inter prediction. One of candidates in the list may be selected for inter prediction for the target block, and inter prediction using the selected candidate may be performed.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a U.S. National Stage Application of InternationalApplication No. PCT/KR2018/011905, filed on Oct. 10, 2018, which claimsthe benefit under 35 USC 119(a) and 365(b) of Korean Patent ApplicationNo. 10-2017-0129156, filed on Oct. 10, 2017, Korean Patent ApplicationNo. 10-2017-0178140, filed on Dec. 22, 2017, Korean Patent ApplicationNo. 10-2018-0071065, filed on Jun. 20, 2018, and Korean PatentApplication No. 10-2018-0120642, filed on Oct. 10, 2018 in the KoreanIntellectual Property Office, the entire disclosure of which isincorporated herein by reference for all purposes.

TECHNICAL FIELD

The following embodiments relate generally to a video decoding methodand apparatus and a video encoding method and apparatus, and moreparticularly, to a method and apparatus that use inter-predictioninformation in video encoding and decoding.

BACKGROUND ART

With the continuous development of the information and communicationindustries, broadcasting services supporting High-Definition (HD)resolution have been popularized all over the world. Through thispopularization, a large number of users have become accustomed tohigh-resolution and high-definition images and/or videos.

To satisfy users' demand for high definition, many institutions haveaccelerated the development of next-generation imaging devices. Users'interest in UHD TVs, having resolution that is more than four times ashigh as that of Full HD (MD) TVs, as well as High-Definition TVs (HDTV)and FHD TVs, has increased. As interest therein has increased, imageencoding/decoding technology for images having higher resolution andhigher definition is continually required.

An image encoding/decoding apparatus and method may use inter-predictiontechnology, intra-prediction technology, entropy-coding technology, etc.so as to perform encoding/decoding on a high-resolution andhigh-definition image. Inter-prediction technology may be technology forpredicting the value of a pixel included in a target picture usingtemporally previous pictures and/or temporally subsequent pictures.Intra-prediction technology may be technology for predicting the valueof a pixel included in a target picture using information about pixelsin the target picture. Entropy-coding technology may be technology forassigning short code words to frequently occurring symbols and assigninglong code words to rarely occurring symbols.

Various prediction methods have been developed to improve the efficiencyand accuracy of intra prediction and/or inter prediction. Predictionefficiency may vary greatly depending on which prediction method amongvarious applicable prediction methods is used for encoding and/ordecoding of a block.

DISCLOSURE Technical Problem

An embodiment is intended to provide an encoding apparatus and methodand a decoding apparatus and method that perform inter prediction for atarget block.

An embodiment is intended to provide an encoding apparatus and methodand a decoding apparatus and method that derive combinedinter-prediction information for a target block and perform interprediction using the derived combined inter-prediction information.

Technical Solution

In accordance with an aspect, there is provided an encoding apparatus,including a processing unit for deriving inter-prediction informationfor a target block and performing inter prediction for the target blockusing the derived inter-prediction information, wherein the processingunit configures a list for the target block using combinedinter-prediction information, and wherein the processing unit generatesthe combined inter-prediction information by combining two or more ofpieces of inter-prediction information of neighbor blocks of the targetblock.

In accordance with another aspect, there is provided a decodingapparatus, including a processing unit for deriving inter-predictioninformation for a target block and performing inter prediction for thetarget block using the derived inter-prediction information, wherein theprocessing unit configures a list for the target block using combinedinter-prediction information, and wherein the processing unit generatesthe combined inter-prediction information by combining two or more ofpieces of inter-prediction information of neighbor blocks of the targetblock.

In accordance with a further aspect, there is provided a decodingmethod, including deriving inter-prediction information for a targetblock; and performing inter prediction for the target block using thederived inter-prediction information, wherein a list for the targetblock is configured using combined inter-prediction information, andwherein the combined inter-prediction information is generated bycombining two or more of pieces of inter-prediction information ofneighbor blocks of the target block.

The inter-prediction information may include at least one of anIllumination Compensation (IC) flag and an Overlapped Block MotionCompensation (OBMC) flag.

The list may be a merge list or an Advanced Motion Vector Prediction(AMVP) list.

The neighbor blocks may include a spatial neighbor block and a temporalneighbor block of the target block.

When inter-prediction information of one of the neighbor blocks isunavailable, combined inter-prediction information for the one neighborblock may be derived.

When inter-prediction information of one of the neighbor blocks is notadded to the list, the combined inter-prediction information derived forthe one neighbor block may be added to the list.

A motion vector of the combined inter-prediction information may be aresult of a formula that uses motion vectors of the neighbor blocks.

The motion vector of the combined inter-prediction information may be aweighted average of the motion vectors of the neighbor blocks.

The motion vector of the combined inter-prediction information may be aresult of a weighted combination of the motion vectors of the neighborblocks based on block size.

The motion vector of the combined inter-prediction information may be aresult of a Picture Order Count (POC)-weighted combination of the motionvectors of the neighbor blocks.

The motion vector of the combined inter-prediction information may be aresult of an extrapolation-based combination of the motion vectors ofthe neighbor blocks.

First inter-prediction information related to a location to left of aspecific block and second inter-prediction information related to alocation to right of the specific block may be derived, and the combinedinter-prediction information may be generated by combining the firstinter-prediction information with the second inter-predictioninformation.

A scheme for configuring the list may be determined based on a shape ofthe target block.

A scheme configuring the list may be determined based on a splittingstate of the target block.

A scheme for configuring the list may be determined based on a locationof the target block.

The combined inter-prediction information may be added to the list witha priority lower than those of pieces of inter-prediction information ofthe neighbor blocks.

The combined inter-prediction information may be added to a location inthe list that is subsequent to inter-prediction information of a spatialneighbor block and is previous to inter-prediction information of atemporal neighbor block.

A scheme for configuring the list may be determined based on a depth ofthe target block.

Advantageous Effects

There are provided an encoding apparatus and method and a decodingapparatus and method that perform inter prediction for a target block.

There are provided an encoding apparatus and method and a decodingapparatus and method that derive combined inter-prediction informationfor a target block and perform inter prediction using the derivedcombined inter-prediction information.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating the configuration of anembodiment of an encoding apparatus to which the present disclosure isapplied;

FIG. 2 is a block diagram illustrating the configuration of anembodiment of a decoding apparatus to which the present disclosure isapplied;

FIG. 3 is a diagram schematically illustrating the partition structureof an image when the image is encoded and decoded;

FIG. 4 is a diagram illustrating the form of a Prediction Unit (PU) thata Coding Unit (CU) can include;

FIG. 5 is a diagram illustrating the form of a Transform Unit (TU) thatcan be included in a CU;

FIG. 6 is a diagram for explaining an embodiment of an intra-predictionprocedure;

FIG. 7 is a diagram for explaining the locations of reference samplesused in an intra-prediction procedure;

FIG. 8 is a diagram for explaining an embodiment of an inter-predictionprocedure;

FIG. 9 illustrates spatial candidates according to an embodiment;

FIG. 10 illustrates the order of addition of motion information ofspatial candidates to a merge list according to an embodiment;

FIG. 11 illustrates a transform and quantization process according to anexample;

FIG. 12 is a configuration diagram of an encoding apparatus according toan embodiment;

FIG. 13 is a configuration diagram of a decoding apparatus according toan embodiment;

FIG. 14 is a flowchart illustrating an inter-prediction method accordingto an embodiment;

FIG. 15 illustrates spatial neighbor blocks of a target block accordingto an example;

FIG. 16 illustrates temporal neighbor blocks of a target block accordingto an example;

FIG. 17 illustrates the generation of combined inter-predictioninformation of an above-right neighbor block according to an example;

FIG. 18 illustrates the generation of combined inter-predictioninformation of an above neighbor block according to an example;

FIG. 19 illustrates the generation of combined inter-predictioninformation of a neighbor block according to an example;

FIG. 20 illustrates the generation of inter-prediction information ofblock AL according to an example;

FIG. 21 illustrates the generation of inter-prediction information ofblock AR according to an example;

FIG. 22 illustrates the generation of inter-prediction information of atarget CU according to an example;

FIG. 23 illustrates the case where a CU of which the width and heightare the same is vertically split;

FIG. 24 illustrates the case where a CU of which the width and heightare the same is horizontally split;

FIG. 25 illustrates the case where a CU having a width greater than aheight is vertically split;

FIG. 26 illustrates the case where a CU having a height greater than awidth is horizontally split;

FIG. 27 illustrates sub-blocks of a temporal neighbor block andsub-blocks of a target block according to an example;

FIG. 28 illustrates spatial neighbor blocks of a target block andsub-blocks of the target block according to an example;

FIG. 29 illustrates the derivation of inter-prediction information usingbilateral matching according to an example;

FIG. 30 illustrates the derivation of inter-prediction information usinga template-matching mode according to an example;

FIG. 31 illustrates the application of OBMC according to an example;

FIG. 32 illustrates sub-PUs in an ATMVP mode according to an example;

FIG. 33 is a flowchart illustrating a target block prediction method anda bitstream generation method according to an embodiment; and

FIG. 34 is a flowchart illustrating a target block prediction methodusing a bitstream according to an embodiment.

BEST MODE

The present invention may be variously changed, and may have variousembodiments, and specific embodiments will be described in detail belowwith reference to the attached drawings. However, it should beunderstood that those embodiments are not intended to limit the presentinvention to specific disclosure forms, and that they include allchanges, equivalents or modifications included in the spirit and scopeof the present invention.

Detailed descriptions of the following exemplary embodiments will bemade with reference to the attached drawings illustrating specificembodiments. These embodiments are described so that those havingordinary knowledge in the technical field to which the presentdisclosure pertains can easily practice the embodiments. It should benoted that the various embodiments are different from each other, but donot need to be mutually exclusive of each other. For example, specificshapes, structures, and characteristics described here may beimplemented as other embodiments without departing from the spirit andscope of the embodiments in relation to an embodiment. Further, itshould be understood that the locations or arrangement of individualcomponents in each disclosed embodiment can be changed without departingfrom the spirit and scope of the embodiments. Therefore, theaccompanying detailed description is not intended to restrict the scopeof the disclosure, and the scope of the exemplary embodiments is limitedonly by the accompanying claims, along with equivalents thereof, as longas they are appropriately described.

In the drawings, similar reference numerals are used to designate thesame or similar functions in various aspects. The shapes, sizes, etc. ofcomponents in the drawings may be exaggerated to make the descriptionclear.

Terms such as “first” and “second” may be used to describe variouscomponents, but the components are not restricted by the terms. Theterms are used only to distinguish one component from another component.For example, a first component may be named a second component withoutdeparting from the scope of the present specification. Likewise, asecond component may be named a first component. The terms “and/or” mayinclude combinations of a plurality of related described items or any ofa plurality of related described items.

It will be understood that when a component is referred to as being“connected” or “coupled” to another component, the two components may bedirectly connected or coupled to each other, or intervening componentsmay be present between the two components. It will be understood thatwhen a component is referred to as being “directly connected orcoupled”, no intervening components are present between the twocomponents.

Also, components described in the embodiments are independently shown inorder to indicate different characteristic functions, but this does notmean that each of the components is formed of a separate piece ofhardware or software. That is, the components are arranged and includedseparately for convenience of description. For example, at least two ofthe components may be integrated into a single component. Conversely,one component may be divided into multiple components. An embodimentinto which the components are integrated or an embodiment in which somecomponents are separated is included in the scope of the presentspecification as long as it does not depart from the essence of thepresent specification.

Further, it should be noted that, in the exemplary embodiments, anexpression describing that a component “comprises” a specific componentmeans that additional components may be included within the scope of thepractice or the technical spirit of exemplary embodiments, but does notpreclude the presence of components other than the specific component.

The terms used in the present specification are merely used to describespecific embodiments and are not intended to limit the presentinvention. A singular expression includes a plural expression unless adescription to the contrary is specifically pointed out in context. Inthe present specification, it should be understood that the terms suchas “include” or “have” are merely intended to indicate that features,numbers, steps, operations, components, parts, or combinations thereofare present, and are not intended to exclude the possibility that one ormore other features, numbers, steps, operations, components, parts, orcombinations thereof will be present or added.

Embodiments will be described in detail below with reference to theaccompanying drawings so that those having ordinary knowledge in thetechnical field to which the embodiments pertain can easily practice theembodiments. In the following description of the embodiments, detaileddescriptions of known functions or configurations which are deemed tomake the gist of the present specification obscure will be omitted.Further, the same reference numerals are used to designate the samecomponents throughout the drawings, and repeated descriptions of thesame components will be omitted.

Hereinafter, “image” may mean a single picture constituting a video, ormay mean the video itself. For example, “encoding and/or decoding of animage” may mean “encoding and/or decoding of a video”, and may also mean“encoding and/or decoding of any one of images constituting the video”.

Hereinafter, the terms “video” and “motion picture” may be used to havethe same meaning, and may be used interchangeably with each other.

Hereinafter, a target image may be an encoding target image, which isthe target to be encoded, and/or a decoding target image, which is thetarget to be decoded. Further, the target image may be an input imagethat is input to an encoding apparatus or an input image that is inputto a decoding apparatus.

Hereinafter, the terms “image”, “picture”, “frame”, and “screen” may beused to have the same meaning and may be used interchangeably with eachother.

Hereinafter, a target block may be an encoding target block, i.e. thetarget to be encoded and/or a decoding target block, i.e. the target tobe decoded. Further, the target block may be a current block, i.e. thetarget to be currently encoded and/or decoded. Here, the terms “targetblock” and “current block” may be used to have the same meaning, and maybe used interchangeably with each other.

Hereinafter, the terms “block” and “unit” may be used to have the samemeaning, and may be used interchangeably with each other. Alternatively,“block” may denote a specific unit.

Hereinafter, the terms “region” and “segment” may be usedinterchangeably with each other.

Hereinafter, a specific signal may be a signal indicating a specificblock. For example, the original signal may be a signal indicating atarget block. A prediction signal may be a signal indicating aprediction block. A residual signal may be a signal indicating aresidual block.

In the following embodiments, specific information, data, a flag, anelement, and an attribute may have their respective values. A value of“0” corresponding to each of the information, data, flag, element, andattribute may indicate a logical false or a first predefined value. Inother words, the value of “0”, false, logical false, and a firstpredefined value may be used interchangeably with each other. A value of“1” corresponding to each of the information, data, flag, element, andattribute may indicate a logical true or a second predefined value. Inother words, the value of “1”, true, logical true, and a secondpredefined value may be used interchangeably with each other.

When a variable such as i or j is used to indicate a row, a column, oran index, the value of i may be an integer of 0 or more or an integer of1 or more. In other words, in the embodiments, each of a row, a column,and an index may be counted from 0 or may be counted from 1.

Below, the terms to be used in embodiments will be described.

Encoder: An encoder denotes a device for performing encoding.

Decoder: A decoder denotes a device for performing decoding.

Unit: A unit may denote the unit of image encoding and decoding. Theterms “unit” and “block” may be used to have the same meaning, and maybe used interchangeably with each other.

-   -   “Unit” may be an M×N array of samples. M and N may be positive        integers, respectively. The term “unit” may generally mean a        two-dimensional (2D) array of samples.    -   In the encoding and decoding of an image, “unit” may be an area        generated by the partitioning of one image. A single image may        be partitioned into multiple units. Alternatively, one image may        be partitioned into sub-parts, and the unit may denote each        partitioned sub-part when encoding or decoding is performed on        the partitioned sub-part.    -   In the encoding and decoding of an image, predefined processing        may be performed on each unit depending on the type of the unit.    -   Depending on functions, the unit types may be classified into a        macro unit, a Coding Unit (CU), a Prediction Unit (PU), a        residual unit, a Transform Unit (TU), etc. Alternatively,        depending on functions, the unit may denote a block, a        macroblock, a coding tree unit (CTU), a coding tree block, a        coding unit, a coding block, a prediction unit, a prediction        block, a residual unit, a residual block, a transform unit, a        transform block, etc.    -   The term “unit” may mean information including a luminance        (luma) component block, a chrominance (chroma) component block        corresponding thereto, and syntax elements for respective blocks        so that the unit is designated to be distinguished from a block.    -   The size and shape of a unit may be variously implemented.        Further, a unit may have any of various sizes and shapes. In        particular, the shapes of the unit may include not only a        square, but also a geometric figure that can be represented in        two dimensions (2D), such as a rectangle, a trapezoid, a        triangle, and a pentagon.    -   Further, unit information may include one or more of the type of        unit, which indicates a coding unit, a prediction unit, a        residual unit or a transform unit, the size of a unit, the depth        of a unit, the order of encoding and decoding of a unit, etc.    -   One unit may be partitioned into sub-units, each having a        smaller size than that of the relevant unit.    -   Depth: A depth may denote the degree to which the unit is        partitioned. Further, the depth may indicate the level at which        the corresponding unit is present when units are represented in        a tree structure.    -   Unit partition information may include a depth indicating the        depth of a unit. A depth may indicate the number of times the        unit is partitioned and/or the degree to which the unit is        partitioned.    -   In a tree structure, it may be considered that the depth of a        root node is the smallest, and the depth of a leaf node is the        largest.    -   A single unit may be hierarchically partitioned into multiple        sub-units while having depth information based on a tree        structure. In other words, the unit and sub-units, generated by        partitioning the unit, may correspond to a node and child nodes        of the node, respectively. Each of the partitioned sub-units may        have a depth. Since the depth indicates the number of times the        unit is partitioned and/or the degree to Which the unit is        partitioned, the partition information of the sub-units may        include information about the sizes of the sub-units.    -   In a tree structure, the top node may correspond to the initial        node before partitioning. The top node may be referred to as a        “root node”. Further, the root node may have a minimum depth        value. Here, the top node may have a depth of level ‘0’.    -   A node having a depth of level ‘1’ may denote a unit generated        when the initial unit is partitioned once. A node having a depth        of level ‘2’ may denote a unit generated when the initial unit        is partitioned twice.    -   A leaf node having a depth of level ‘n’ may denote a unit        generated when the initial unit has been partitioned n times.    -   The leaf node may be a bottom node, which cannot be partitioned        any further. The depth of the leaf node may be the maximum        level. For example, a predefined value for the maximum level may        be 3.    -   QT depth may denote the depth of quad-splitting. BT depth may        denote the depth of binary-splitting. TT depth may denote the        depth of triple-splitting.

Sample: A sample may be a base unit constituting a block. A sample maybe represented by values from 0 to 2^(Bd−)1 depending on the bit depth(Bd).

-   -   A sample may be a pixel or a pixel value.    -   Hereinafter, the terms “pixel” and “sample” may be used to have        the same meaning, and may be used interchangeably with each        other.

A Coding Tree Unit (CTU): A. CTU may be composed of a single lumacomponent (Y) coding tree block and two chroma component (Cb, Cr) codingtree blocks related to the lama component coding tree block. Further, aCTU may mean information including the above blocks and a syntax elementfor each of the blocks.

-   -   Each coding tree unit (CTU) may be partitioned using one or more        partitioning methods, such as a quad tree (QT), a binary tree        (BT) and a ternary tree (TT), so as to configure sub-units, such        as a coding unit, a prediction unit, and a transform unit.    -   “CTU” may be used as a term designating a pixel block, which is        a processing unit in an image-decoding and encoding process, as        in the case of partitioning of an input image.

Coding Tree Block (CTB): “CTB” may be used as a term designating any oneof a Y coding tree block, a Cb coding tree block, and a Cr coding treeblock.

-   -   Neighbor (neighboring) block: A neighbor block means a block        adjacent to a target block. The term “neighbor block” may also        refer to a reconstructed neighbor block.

Hereinafter, the terms “neighbor block” and “adjacent block” may be usedto have the same meaning, and may be used interchangeably with eachother.

-   -   Spatial neighbor block: A spatial neighbor block may be a block        spatially adjacent to a target block. Neighbor blocks may        include spatial neighbor blocks.    -   A target block and a spatial neighbor block may be included in a        target picture.    -   A spatial neighbor block may be either a block, the boundary of        which meets a target block, or a block located at a        predetermined distance from the target block.    -   A spatial neighbor block may be a block adjacent to the vertex        of a target block. Here, the block adjacent to the vertex of the        target block may be either a block vertically adjacent to a        neighbor block that is horizontally adjacent to the target        block, or a block horizontally adjacent to a neighbor block that        is vertically adjacent to the target block.

A temporal neighbor block: A temporal neighbor block may be a blocktemporally adjacent to a target block. Neighbor blocks may include thetemporal neighbor block.

-   -   A temporal neighbor block may include a co-located block (col        block).    -   A col block may be a block in a previously reconstructed        co-located picture (col picture). The location of the col block        in the col picture may correspond to the location of a target        block in a target picture. The col picture may be a picture        included in a reference picture list.    -   A temporal neighbor block may be a spatial neighbor block of a        target block.

Prediction unit: A prediction unit may be a base unit for prediction,such as inter prediction, intra prediction, inter compensation, intracompensation, and motion compensation.

-   -   A single prediction unit may be divided into multiple partitions        having smaller sizes or sub-prediction units. The multiple        partitions may also be base units in the performance of        prediction or compensation. The partitions generated by dividing        the prediction unit may also be prediction units.

Prediction unit partition: A prediction unit partition may be the shapeinto which a prediction unit is divided.

Reconstructed neighboring unit: A reconstructed neighboring unit may bea unit which has already been decoded and reconstructed around a targetunit.

-   -   A reconstructed neighboring unit may be a unit that is spatially        adjacent to the target unit or that is temporally adjacent to        the target unit.    -   A reconstructed spatially neighboring unit may be a unit which        is included in a target picture and which has already been        reconstructed through encoding and/or decoding.    -   A reconstructed temporally neighboring unit may be a unit which        is included in a reference image and which has already been        reconstructed through encoding and/or decoding. The location of        the reconstructed temporally neighboring unit in the reference        image may be identical to that of the target unit in the target        picture, or may correspond to the location of the target unit in        the target picture.

Parameter set: A parameter set may be header information in thestructure of a bitstream. For example, a parameter set may include asequence parameter set, a picture parameter set, an adaptation parameterset, etc.

Rate-distortion optimization: An encoding apparatus may userate-distortion optimization so as to provide high coding efficiency byutilizing combinations of the size of a coding unit (CU), a predictionmode, the size of a prediction unit (PU), motion information, and thesize of a transform unit (TU).

-   -   A rate-distortion optimization scheme may calculate        rate-distortion costs of respective combinations so as to select        an optimal combination from among the combinations. The        rate-distortion costs may be calculated using the following        Equation 1. Generally, a combination enabling the        rate-distortion cost to be minimized may be selected as the        optimal combination in the rate-distortion optimization scheme.        D+λ*R  [Equation 1]    -   D may denote distortion. D may be the mean of squares of        differences (i.e. mean square error) between original transform        coefficients and reconstructed transform coefficients in a        transform unit.    -   R may denote the rate, which may denote a bit rate using        related-context information.    -   λ denotes a Lagrangian multiplier. R may include not only coding        parameter information, such as a prediction mode, motion        information, and a coded block flag, but also bits generated due        to the encoding of transform coefficients.    -   An encoding apparatus may perform procedures, such as inter        prediction and/or intra prediction, transform, quantization,        entropy encoding, inverse quantization (dequantization), and        inverse transform so as to calculate precise D and R. These        procedures may greatly increase the complexity of the encoding        apparatus.    -   Bitstream: A bitstream may denote a stream of bits including        encoded image information.    -   Parameter set: A parameter set may be header information in the        structure of a bitstream.    -   The parameter set may include at least one of a video parameter        set, a sequence parameter set, a picture parameter set, and an        adaptation parameter set. Further, the parameter set may include        information about a slice header and information about a tile        header.

Parsing: Parsing may be the decision on the value of a syntax element,made by performing entropy decoding on a bitstream. Alternatively, theterm “parsing” may mean such entropy decoding itself.

Symbol: A symbol may be at least one of the syntax element, the codingparameter, and the transform coefficient of an encoding target unitand/or a decoding target unit. Further, a symbol may be the target ofentropy encoding or the result of entropy decoding.

Reference picture: A reference picture may be an image referred to by aunit so as to perform inter prediction or motion compensation.Alternatively, a reference picture may be an image including a referenceunit referred to by a target unit so as to perform inter prediction ormotion compensation.

Hereinafter, the terms “reference picture” and “reference image” may beused to have the same meaning, and may be used interchangeably with eachother.

Reference picture list: A reference picture list may be a list includingone or more reference images used for inter prediction or motioncompensation.

-   -   The types of a reference picture list may include List Combined        (LC), List 0 (L0), List 1 (L1), List 2 (L2), List 3 (L3), etc.    -   For inter prediction, one or more reference picture lists may be        used.

Inter-prediction indicator: An inter-prediction indicator may indicatethe inter-prediction direction of a target unit. Inter prediction may beone of unidirectional prediction and bidirectional prediction.Alternatively, the inter-prediction indicator may denote the number ofreference images used to generate a prediction unit of a target unit.Alternatively, the inter-prediction indicator may denote the number ofprediction blocks used for inter prediction or motion compensation of atarget unit.

Reference picture index: A reference picture index may be an indexindicating a specific reference image in a reference picture list.

Motion vector (MV): A motion vector may be a 2D vector used for interprediction or motion compensation. A motion vector may mean an offsetbetween an encoding target image/decoding target image and a referenceimage.

-   -   For example, a MV may be represented in a form such as (mv_(x),        mv_(y)), mv_(x) may indicate a horizontal component, and mv_(y)        may indicate a vertical component.    -   Search range: A search range may be a 2D area in which a search        for a MV is performed during inter prediction. For example, the        size of the search range may be M×N. M and N may be respective        positive integers.

Motion vector candidate: A motion vector candidate may be a block thatis a prediction candidate or the motion vector of the block that is aprediction candidate when a motion vector is predicted.

-   -   A motion vector candidate may be included in a motion vector        candidate list.

Motion vector candidate list: A motion vector candidate list may be alist configured using one or more motion vector candidates.

Motion vector candidate index: A motion vector candidate index may be anindicator for indicating a motion vector candidate in the motion vectorcandidate list. Alternatively, a motion vector candidate index may bethe index of a motion vector predictor.

Motion information: Motion information may be information including atleast one of a reference picture list, a reference image, a motionvector candidate, a motion vector candidate index, a merge candidate,and a merge index, as well as a motion vector, a reference pictureindex, and an inter-prediction indicator.

Merge candidate list: A merge candidate list may be a list configuredusing merge candidates.

Merge candidate: A merge candidate may be a spatial merge candidate, atemporal merge candidate, a combined merge candidate, a combinedbi-prediction merge candidate, a zero-merge candidate, etc. A mergecandidate may include motion information such as an inter-predictionindicator, a reference picture index for each list, and a motion vector.

Merge index: A merge index may be an indicator for indicating a mergecandidate in a merge candidate list.

-   -   A merge index may indicate a reconstructed unit used to derive a        merge candidate between a reconstructed unit spatially adjacent        to a target unit and a reconstructed unit temporally adjacent to        the target unit.    -   A merge index may indicate at least one of pieces of motion        information of a merge candidate.

Transform unit: A transform unit may be the base unit of residual signalencoding and/or residual signal decoding, such as transform, inversetransform, quantization, dequantization, transform coefficient encoding,and transform coefficient decoding. A single transform unit may bepartitioned into multiple transform units having smaller sizes.

Scaling: Scaling may denote a procedure for multiplying a factor by atransform coefficient level.

-   -   As a result of scaling of the transform coefficient level, a        transform coefficient may be generated. Scaling may also be        referred to as “dequantization”.

Quantization Parameter (QP): A quantization parameter may be a valueused to generate a transform coefficient level for a transformcoefficient in quantization. Alternatively, a quantization parameter mayalso be a value used to generate a transform coefficient by scaling thetransform coefficient level in dequantization. Alternatively, aquantization parameter may be a value mapped to a quantization stepsize.

Delta quantization parameter: A delta quantization parameter is adifferential value between a predicted quantization parameter and thequantization parameter of an encoding/decoding target unit.

Scan: Scan may denote a method for aligning the order of coefficients ina unit, a block or a matrix. For example, a method for aligning a 2Darray in the form of a one-dimensional (1D) array may be referred to asa “scan”. Alternatively, a method for aligning a 1D array in the form ofa 2D array may also be referred to as a “scan” or an “inverse scan”.

Transform coefficient: A transform coefficient may be a coefficientvalue generated as an encoding apparatus performs a transform.Alternatively, the transform coefficient may be a coefficient valuegenerated as a decoding apparatus performs at least one of entropydecoding and dequantization.

-   -   A quantized level or a quantized transform coefficient level in        which quantization is applied to a transform coefficient or a        residual signal may also be included in the meaning of the term        “transform coefficient”.

Quantized level: A quantized level may be a value generated as theencoding apparatus performs quantization on a transform coefficient or aresidual signal. Alternatively, the quantized level may be a value thatis the target of dequantization as the decoding apparatus performsdequantization.

-   -   A quantized transform coefficient level, which is the result of        transform and quantization, may also be included in the meaning        of a quantized level.

Non-zero transform coefficient: A non-zero transform coefficient may bea transform coefficient having a value other than 0 or a transformcoefficient level having a value other than 0. Alternatively, a non-zerotransform coefficient may be a transform coefficient, the magnitude ofthe value of which is not 0, or a transform coefficient level, themagnitude of the value of which is not 0.

Quantization matrix: A quantization matrix may be a matrix used in aquantization or dequantization procedure so as to improve the subjectiveimage quality or objective image quality of an image. A quantizationmatrix may also be referred to as a “scaling list”.

Quantization matrix coefficient: A quantization matrix coefficient maybe each element in a quantization matrix. A quantization matrixcoefficient may also be referred to as a “matrix coefficient”.

Default matrix: A default matrix may be a quantization matrix predefinedby the encoding apparatus and the decoding apparatus.

Non-default matrix: A non-default matrix may be a quantization matrixthat is not predefined by the encoding apparatus and the decodingapparatus. The non-default matrix may be signaled by the encodingapparatus to the decoding apparatus.

Signaling: Signaling may indicate that information is transmitted froman encoding apparatus to a decoding apparatus. Alternatively, signalingmay mean that information is included in a bitstream or a storagemedium. The information signaled by the encoding apparatus may be usedby the decoding apparatus.

FIG. 1 is a block diagram illustrating the configuration of anembodiment of an encoding apparatus to which the present disclosure isapplied.

An encoding apparatus 100 may be an encoder, a video encoding apparatusor an image encoding apparatus. A video may include one or more images(pictures). The encoding apparatus 100 may sequentially encode one ormore images of the video.

Referring to FIG. 1, the encoding apparatus 100 includes aninter-prediction unit 110, an intra-prediction unit 120, a switch 115, asubtractor 125, a transform unit 130, a quantization unit 140, anentropy encoding unit 150, a dequantization (inverse quantization) unit160, an inverse transform unit 170, an adder 175, a filter unit 180, anda reference picture buffer 190.

The encoding apparatus 100 may perform encoding on a target image usingan intra mode and/or an inter mode.

Further, the encoding apparatus 100 may generate a bitstream, includinginformation about encoding, via encoding on the target image, and mayoutput the generated bitstream. The generated bitstream may be stored ina computer-readable storage medium and may be streamed through awired/wireless transmission medium.

When the intra mode is used as a prediction mode, the switch 115 mayswitch to the intra mode. When the inter mode is used as a predictionmode, the switch 115 may switch to the inter mode.

The encoding apparatus 100 may generate a prediction block of a targetblock. Further, after the prediction block has been generated, theencoding apparatus 100 may encode a residual between the target blockand the prediction block.

When the prediction mode is the intra mode, the intra-prediction unit120 may use pixels of previously encoded/decoded neighboring blocksaround the target block as reference samples. The intra-prediction unit120 may perform spatial prediction on the target block using thereference samples, and may generate prediction samples for the targetblock via spatial prediction.

The inter-prediction unit 110 may include a motion prediction unit and amotion compensation unit.

When the prediction mode is an inter mode, the motion prediction unitmay search a reference image for the area most closely matching thetarget block in a motion prediction procedure, and may derive a motionvector for the target block and the found area based on the found area.

The reference image may be stored in the reference picture buffer 190.More specifically, the reference image may be stored in the referencepicture buffer 190 when the encoding and/or decoding of the referenceimage have been processed.

The motion compensation unit may generate a prediction block for thetarget block by performing motion compensation using a motion vector.Here, the motion vector may be a two-dimensional (2D) vector used forinter-prediction. Further, the motion vector may indicate an offsetbetween the target image and the reference image.

The motion prediction unit and the motion compensation unit may generatea prediction block by applying an interpolation filter to a partial areaof a reference image when the motion vector has a value other than aninteger. In order to perform inter prediction or motion compensation, itmay be determined which one of a skip mode, a merge mode, an advancedmotion vector prediction (AMVP) mode, and a current picture referencemode corresponds to a method for predicting the motion of a PU includedin a CU, based on the CU, and compensating for the motion, and interprediction or motion compensation may be performed depending on themode.

The subtractor 125 may generate a residual block, which is thedifferential between the target block and the prediction block. Aresidual block may also be referred to as a “residual signal”.

The residual signal may be the difference between an original signal anda prediction signal. Alternatively, the residual signal may be a signalgenerated by transforming or quantizing the difference between anoriginal signal and a prediction signal or by transforming andquantizing the difference. A residual block may be a residual signal fora block unit.

The transform unit 130 may generate a transform coefficient bytransforming the residual block, and may output the generated transformcoefficient. Here, the transform coefficient may be a coefficient valuegenerated by transforming the residual block.

When a transform skip mode is used, the transform unit 130 may omittransforming the residual block.

By applying quantization to the transform coefficient, a quantizedtransform coefficient level or a quantized level may be generated.Hereinafter, in the embodiments, each of the quantized transformcoefficient level and the quantized level may also be referred to as a‘transform coefficient’.

The quantization unit 140 may generate a quantized transform coefficientlevel or a quantized level by quantizing the transform coefficientdepending on quantization parameters. The quantization unit 140 mayoutput the quantized transform coefficient level or the quantized levelthat is generated. In this case, the quantization unit 140 may quantizethe transform coefficient using a quantization matrix.

The entropy encoding unit 150 may generate a bitstream by performingprobability distribution-based entropy encoding based on values,calculated by the quantization unit 140, and/or coding parameter values,calculated in the encoding procedure. The entropy encoding unit 150 mayoutput the generated bitstream.

The entropy encoding unit 150 may perform entropy encoding oninformation about the pixels of the image and information required todecode the image. For example, the information required to decode theimage may include syntax elements or the like.

The coding parameters may be information required for encoding and/ordecoding. The coding parameters may include information encoded by theencoding apparatus 100 and transferred from the encoding apparatus 100to a decoding apparatus, and may also include information that may bederived in the encoding or decoding procedure. For example, informationtransferred to the decoding apparatus may include syntax elements.

For example, the coding parameters may include values or statisticalinformation, such as a prediction mode, a motion vector, a referencepicture index, an encoding block pattern, the presence or absence of aresidual signal, a transform coefficient, a quantized transformcoefficient, a quantization parameter, a block size, and block partitioninformation. The prediction mode may be an intra-prediction mode or aninter-prediction mode.

The residual signal may denote the difference between the originalsignal and a prediction signal. Alternatively, the residual signal maybe a signal generated by transforming the difference between theoriginal signal and the prediction signal. Alternatively, the residualsignal may be a signal generated by transforming and quantizing thedifference between the original signal and the prediction signal.

When entropy encoding is applied, fewer bits may be assigned to morefrequently occurring symbols, and more bits may be assigned to rarelyoccurring symbols. As symbols are represented by means of thisassignment, the size of a bit string for target symbols to be encodedmay be reduced. Therefore, the compression performance of video encodingmay be improved through entropy encoding.

Further, for entropy encoding, the entropy encoding unit 150 may use acoding method such as exponential Golomb, Context-Adaptive VariableLength Coding (CAVLC), or Context-Adaptive Binary Arithmetic Coding(CABAC). For example, the entropy encoding unit 150 may perform entropyencoding using a Variable Length Coding/Code (VLC) table. For example,the entropy encoding unit 150 may derive a binarization method for atarget symbol. Further, the entropy encoding unit 150 may derive aprobability model for a target symbol/bin. The entropy encoding unit 150may perform arithmetic coding using the derived binarization method, aprobability model, and a context model.

The entropy encoding unit 150 may transform the coefficient of the formof a 2D block into the form of a 1D vector through a transformcoefficient scanning method so as to encode a transform coefficientlevel.

The coding parameters may include not only information (or a flag or anindex), such as a syntax element, which is encoded by the encodingapparatus and is signaled by the encoding apparatus to the decodingapparatus, but also information derived in an encoding or decodingprocess. Further, the coding parameters may include information requiredso as to encode or decode images. For example, the coding parameters mayinclude at least one or combinations of the size of a unit/block, thedepth of a unit/block, partition information of a unit/block, thepartition structure of a unit/block, information indicating whether aunit/block is partitioned in a quad-tree structure, informationindicating whether a unit/block is partitioned in a binary tree (BT)structure, the partitioning direction of a binary tree structure(horizontal direction or vertical direction), the partitioning form of abinary tree structure (symmetrical partitioning or asymmetricalpartitioning), information indicating whether a unit/block ispartitioned in a ternary tree structure, the partitioning direction of aternary tree structure (horizontal direction or vertical direction), aprediction scheme (intra prediction or inter prediction), anintra-prediction mode/direction, a reference sample filtering method, aprediction block filtering method, a prediction block boundary filteringmethod, a filter tap for filtering, a filter coefficient for filtering,an inter-prediction mode, motion information, a motion vector, areference picture index, an inter-prediction direction, aninter-prediction indicator, a reference picture list, a reference image,a motion vector predictor, a motion vector prediction candidate, amotion vector candidate list, information indicating whether a mergemode is used, a merge candidate, a merge candidate list, informationindicating whether a skip mode is used, the type of an interpolationfilter, the tap of an interpolation filter, the filter coefficient of aninterpolation filter, the magnitude of a motion vector, accuracy ofmotion vector representation, a transform type, a transform size,information indicating whether a primary transform is used, informationindicating whether an additional (secondary) transform is used, aprimary transform index, a secondary transform index, informationindicating the presence or absence of a residual signal, a coded blockpattern, a coded block flag, a quantization parameter, a quantizationmatrix, information about an intra-loop filter, information indicatingwhether an intra-loop filter is applied, the coefficient of anintra-loop filter, the tap of an intra-loop filter, the shape/form of anintra-loop filter, information indicating whether a deblocking filter isapplied, the coefficient of a deblocking filter, the tap of a deblockingfilter, deblocking filter strength, the shape/form of a deblockingfilter, information indicating whether an adaptive sample offset isapplied, the value of an adaptive sample offset, the category of anadaptive sample offset, the type of an adaptive sample offset,information indicating whether an adaptive in-loop filter is applied,the coefficient of an adaptive in-loop filter, the tap of an adaptivein-loop filter, the shape/form of an adaptive in-loop filter, abinarization/inverse binarization method, a context model, a contextmodel decision method, a context model update method, informationindicating whether a regular mode is performed, information whether abypass mode is performed, a context bin, a bypass bin, a transformcoefficient, a transform coefficient level, a transform coefficientlevel scanning method, an image display/output order, sliceidentification information, a slice type, slice partition information,tile identification information, a tile type, tile partitioninformation, a picture type, bit depth, information about a luma signal,and information about a chroma signal.

Here, signaling a flag or an index may mean that the encoding apparatus100 includes an entropy-encoded flag or an entropy-encoded index,generated by performing entropy encoding on the flag or index, in abitstream, and that the decoding apparatus 200 acquires a flag or anindex by performing entropy decoding on the entropy-encoded flag or theentropy-encoded index, extracted from the bitstream.

Since the encoding apparatus 100 performs encoding via inter prediction,the encoded target image may be used as a reference image for additionalimage(s) to be subsequently processed. Therefore, the encoding apparatus100 may reconstruct or decode the encoded target image and store thereconstructed or decoded image as a reference image in the referencepicture buffer 190. For decoding, dequantization and inverse transformon the encoded target image may be processed.

The quantized level may be inversely quantized by the dequantizationunit 160, and may be inversely transformed by the inverse transform unit170. The coefficient that has been inversely quantized and/or inverselytransformed may be added to the prediction block by the adder 175. Theinversely quantized and/or inversely transformed coefficient and theprediction block are added, and then a reconstructed block may begenerated. Here, the inversely quantized and/or inversely transformedcoefficient may denote a coefficient on which one or more ofdequantization and inverse transform are performed, and may also denotea reconstructed residual block.

The reconstructed block may be subjected to filtering through the filterunit 180. The filter unit 180 may apply one or more of a deblockingfilter, a Sample Adaptive Offset (SAO) filter, and an Adaptive LoopFilter (ALF) to the reconstructed block or a reconstructed picture. Thefilter unit 180 may also be referred to as an “in-loop filter”.

The deblocking filter may eliminate block distortion occurring at theboundaries between blocks. In order to determine whether to apply thedeblocking filter, the number of columns or rows which are included in ablock and which include pixel(s) based on which it is determined whetherto apply the deblocking filter to a target block may be decided on. Whenthe deblocking filter is applied to the target block, the applied filtermay differ depending on the strength of the required deblockingfiltering. In other words, among different filters, a filter decided onin consideration of the strength of deblocking filtering may be appliedto the target block.

The SAO may add a suitable offset to the values of pixels to compensatefor coding error. The SAO may perform, for the image to which deblockingis applied, correction that uses an offset in the difference between anoriginal image and the image to which deblocking is applied, on a pixelbasis. A method for dividing the pixels included in the image into acertain number of regions, determining a region to which an offset is tobe applied, among the divided regions, and applying an offset to thedetermined region may be used, and a method for applying an offset inconsideration of edge information of each pixel may also be used.

The ALF may perform filtering based on a value obtained by comparing areconstructed image with an original image. After pixels included in animage have been divided into a predetermined number of groups, filtersto be applied to the groups may be determined, and filtering may bedifferentially performed for respective groups. Information related towhether to apply an adaptive loop filter may be signaled for each CU.The shapes and filter coefficients of ALFs to be applied to respectiveblocks may differ for respective blocks.

The reconstructed block or the reconstructed image subjected tofiltering through the filter unit 180 may be stored in the referencepicture buffer 190. The reconstructed block subjected to filteringthrough the filter unit 180 may be a part of a reference picture. Inother words, the reference picture may be a reconstructed picturecomposed of reconstructed blocks subjected to filtering through thefilter unit 180. The stored reference picture may be subsequently usedfor inter prediction.

FIG. 2 is a block diagram illustrating the configuration of anembodiment of a decoding apparatus to which the present disclosure isapplied.

A decoding apparatus 200 may be a decoder, a video decoding apparatus oran image decoding apparatus.

Referring to FIG. 2, the decoding apparatus 200 may include an entropydecoding unit 210, a dequantization (inverse quantization) unit 220, aninverse transform unit 230, an intra-prediction unit 240, aninter-prediction unit 250, an adder 255, a filter unit 260, and areference picture buffer 270.

The decoding apparatus 200 may receive a bitstream output from theencoding apparatus 100. The decoding apparatus 200 may receive abitstream stored in a computer-readable storage medium, and may receivea bitstream that is streamed through a wired/wireless transmissionmedium.

The decoding apparatus 200 may perform decoding on the bitstream in anintra mode and/or an inter mode. Further, the decoding apparatus 200 maygenerate a reconstructed image or a decoded image via decoding, and mayoutput the reconstructed image or decoded image.

For example, switching a mode or an inter mode based on the predictionmode used for decoding may be performed by a switch. When the predictionmode used for decoding is an intra mode, the switch may be operated toswitch to the intra mode. When the prediction mode used for decoding isan inter mode, the switch may be operated to switch to the inter mode.

The decoding apparatus 200 may acquire a reconstructed residual block bydecoding the input bitstream, and may generate a prediction block. Whenthe reconstructed residual block and the prediction block are acquired,the decoding apparatus 200 may generate a reconstructed block, which isthe target to be decoded, by adding the reconstructed residual block tothe prediction block.

The entropy decoding unit 210 may generate symbols by performing entropydecoding on the bitstream based on the probability distribution of abitstream. The generated symbols may include quantized level-formatsymbols. Here, the entropy decoding method may be similar to theabove-described entropy encoding method. That is, the entropy decodingmethod may be the reverse procedure of the above-described entropyencoding method.

The quantized coefficient may be inversely quantized by thedequantization unit 220. The dequantization unit 220 may generate aninversely quantized coefficient by performing dequantization on thequantized coefficient. Further, the inversely quantized coefficient maybe inversely transformed by the inverse transform unit 230. The inversetransform unit 230 may generate a reconstructed residual block byperforming an inverse transform on the inversely quantized coefficient.As a result of performing dequantization and the inverse transform onthe quantized coefficient, the reconstructed residual block may begenerated. Here, the dequantization unit 220 may apply a quantizationmatrix to the quantized coefficient when generating the reconstructedresidual block.

When the intra mode is used, the intra-prediction unit 240 may generatea prediction block by performing spatial prediction that uses the pixelvalues of previously decoded neighboring blocks around a target block.

The inter-prediction unit 250 may include a motion compensation unit.Alternatively, the inter-prediction unit 250 may be designated as a“motion compensation unit”.

When the inter mode is used, the motion compensation unit may generate aprediction block by performing motion compensation that uses a motionvector and a reference image stored in the reference picture buffer 270.

The motion compensation unit may apply an interpolation filter to apartial area of the reference image when the motion vector has a valueother than an integer, and may generate a prediction block using thereference image to which the interpolation filter is applied. In orderto perform motion compensation, the motion compensation unit maydetermine which one of a skip mode, a merge mode, an Advanced MotionVector Prediction (AMVP) mode, and a current picture reference modecorresponds to the motion compensation method used for a PU included ina CU, based on the CU, and may perform motion compensation depending onthe determined mode.

The reconstructed residual block and the prediction block may be addedto each other by the adder 255. The adder 255 may generate areconstructed block by adding the reconstructed residual block to theprediction block.

The reconstructed block may be subjected to filtering through the filterunit 260. The filter unit 260 may apply at least one of a deblockingfilter, an SAO filter, and an ALF to the reconstructed block or thereconstructed picture.

The reconstructed block subjected to filtering through the filter unit260 may be stored in the reference picture buffer 270. The reconstructedblock subjected to filtering through the filter unit 260 may be a pailof a reference picture. In other words, the reference image may be animage composed of reconstructed blocks subjected to filtering throughthe filter unit 260. The stored reference image may be subsequently usedfor inter prediction.

FIG. 3 is a diagram schematically illustrating the partition structureof an image when the image is encoded and decoded.

FIG. 3 may schematically illustrate an example in which a single unit ispartitioned into multiple sub-units.

In order to efficiently partition the image, a Coding Unit (CU) may beused in encoding and decoding. The term “unit” may be used tocollectively designate 1) a block including image samples and 2) asyntax element. For example, the “partitioning of a unit” may mean the“partitioning of a block corresponding to a unit”.

A CU may be used as a base unit for image encoding/decoding. A CU may beused as a unit to which one mode selected from an intra mode and aninter mode in image encoding/decoding is applied. In other words, inimage encoding/decoding, which one of an intra mode and an inter mode isto be applied to each CU may be determined.

Further, a CU may be a base unit in prediction, transform, quantization,inverse transform, dequantization, and encoding/decoding of transformcoefficients,

Referring to FIG. 3, an image 200 may be sequentially partitioned intounits corresponding to a Largest Coding Unit (LCU), and the partitionstructure of the image 300 may be determined according to the LCU. Here,the LCU may be used to have the same meaning as a Coding Tree Unit(CTU).

The partitioning of a unit may mean the partitioning of a blockcorresponding to the unit. Block partition information may include depthinformation about the depth of a unit. The depth information mayindicate the number of times the unit is partitioned and/or the degreeto which the unit is partitioned. A single unit may be hierarchicallypartitioned into sub-units while having depth information based on atree structure. Each of partitioned sub-units may have depthinformation. The depth information may be information indicating thesize of a CU. The depth information may be stored for each CU. Each CUmay have depth information.

The partition structure may mean the distribution of Coding Units (CUs)to efficiently encode the image in an LCU 310. Such a distribution maybe determined depending on whether a single CU is to be partitioned intomultiple CUs. The number of CUs generated by partitioning may be apositive integer of 2 or more, including 2, 4, 8, 16, etc. Thehorizontal size and the vertical size of each of CUs generated by thepartitioning may be less than the horizontal size and the vertical sizeof a CU before being partitioned, depending on the number of CUsgenerated by partitioning.

Each partitioned CU may be recursively partitioned into four CUs in thesame way. Via the recursive partitioning, at least one of the horizontalsize and the vertical size of each partitioned CU may be reducedcompared to at least one of the horizontal size and the vertical size ofthe CU before being partitioned.

The partitioning of a CU may be recursively performed up to a predefineddepth or a predefined size. For example, the depth of an LCU may be 0,and the depth of a Smallest Coding Unit (SCU) may be a predefinedmaximum depth. Here, as described above, the LCU may be the CU havingthe maximum coding unit size, and the SCU may be the CU having theminimum coding unit size.

Partitioning may start at the LCU 310, and the depth of a CU may beincreased by 1 whenever the horizontal and/or vertical sizes of the CUare reduced by partitioning.

For example, for respective depths, a CU that is not partitioned mayhave a size of 2N×2N. Further, in the case of a CU that is partitioned,a CU having a size of 2N×2N may be partitioned into four CUs, eachhaving a size of N×N. The value of N may be halved whenever the depth isincreased by 1.

Referring to FIG. 3, an LCU having a depth of 0 may have 64×64 pixels or64×64 blocks. 0 may be a minimum depth. An SCU having a depth of 3 mayhave 8×8 pixels or 8×8 blocks. 3 may be a maximum depth. Here, a CUhaving 64×64 blocks, which is the LCU, may be represented by a depth of0. A CU having 32×32 blocks may be represented by a depth of 1. A CUhaving 16×16 blocks may be represented by a depth of 2. A CU having 8×8blocks, which is the SCU, may be represented by a depth of 3.

Information about whether the corresponding CU is partitioned may berepresented by the partition information of the CU. The partitioninformation may be 1-bit information. All CUs except the SCU may includepartition information. For example, the value of the partitioninformation of a CU that is not partitioned may be 0. The value of thepartition information of a CU that is partitioned may be 1.

For example, when a single CU is partitioned into four CUs, thehorizontal size and vertical size of each of four CUs generated bypartitioning may be half the horizontal size and the vertical size ofthe CU before being partitioned. When a CU having a 32×32 size ispartitioned into four CUs, the size of each of four partitioned CUs maybe 16×16. When a single CU is partitioned into four CUs, it may beconsidered that the CU has been partitioned in a quad-tree structure.

For example, when a single CU is partitioned into two CUs, thehorizontal size or the vertical size of each of two CUs generated bypartitioning may be half the horizontal size or the vertical size of theCU before being partitioned. When a CU having a 32×32 size is verticallypartitioned into two CUs, the size of each of two partitioned CUs may be16×32. When a single CU is partitioned into two CUs, it may beconsidered that the CU has been partitioned in a binary-tree structure.

Both of quad-tree partitioning and binary-tree partitioning are appliedto the LCU 310 of FIG. 3.

FIG. 4 is a diagram illustrating the form of a Prediction Unit (PU) thata Coding Unit (CU) can include.

When, among CUs partitioned from an LCU, a CU, which is not partitionedany further, may be divided into one or more Prediction Units (PUs).Such division is also referred to as “partitioning”.

A PU may be a base unit for prediction. A PU may be encoded and decodedin any one of a skip mode, an inter mode, and an intra mode. A PU may bepartitioned into various shapes depending on respective modes. Forexample, the target block, described above with reference to FIG. 1, andthe target block, described above with reference to FIG. 2, may each bea PU.

In a skip mode, partitioning may not be present in a CU. In the skipmode, a 2N×2N mode 410, in which the sizes of a PU and a CU areidentical to each other, may be supported without partitioning.

In an inter mode, 8 types of partition shapes may be present in a CU.For example, in the inter mode, the 2N×2N mode 410, a 2N×N mode 415, anN×2N mode 420, an N×N mode 425, a 2N×nL mode 430, a 2N×nD mode 435, annL×2N mode 440, and an nR×2N mode 445 may be supported.

In an intra mode, the 2N×2N mode 410 amd the N×N mode 425 may besupported.

In the 2N×2N mode 410, a PU having a size of 2N×2N may be encoded. ThePU having a size of 2N×2N may mean a PU having a size identical to thatof the CU. For example, the PU having a size of 2N×2N may have a size of64×64, 32×32, 16×16 or 8×8.

In the N×N mode 425, a PU having a size of N×N may be encoded.

For example, in intra prediction, when the size of a PU is 8×8, fourpartitioned PUs may be encoded. The size of each partitioned PU may be4×4.

When a PU is encoded in an intra mode, the PU may be encoded using anyone of multiple intra-prediction modes. For example, HEVC technology mayprovide 35 intra-prediction modes, and the PU may be encoded in any oneof the 35 intra-prediction modes.

Which one of the 2N×2N mode 410 and the N×N mode 425 is to be used toencode the PU may be determined based on rate-distortion cost.

The encoding apparatus 100 may perform an encoding operation on a PUhaving a size of 2N×2N. Here, the encoding operation may be theoperation of encoding the PU in each of multiple intra-prediction modesthat can be used by the encoding apparatus 100. Through the encodingoperation, the optimal intra-prediction mode for a PU having a size of2N×2N may be derived. The optimal intra-prediction mode may be anintra-prediction mode in which a minimum rate-distortion cost occursupon encoding the PU having a size of 2N×2N, among multipleintra-prediction modes that can be used by the encoding apparatus 100.

Further, the encoding apparatus 100 may sequentially perform an encodingoperation on respective PUs obtained from N×N partitioning. Here, theencoding operation may be the operation of encoding a PU in each ofmultiple intra-prediction modes that can be used by the encodingapparatus 100. By means of the encoding operation, the optimalintra-prediction mode for the PU having a size of N×N may be derived.The optimal intra-prediction mode may be an intra-prediction mode inwhich a minimum rate-distortion cost occurs upon encoding the PU havinga size of N×N, among multiple intra-prediction modes that can be used bythe encoding apparatus 100.

The encoding apparatus 100 may determine which of a PU having a size of2N×2N and PUs having sizes of N×N to be encoded based on a comparison ofa rate-distortion cost of the PU having a size of 2N×2N and arate-distortion costs of the PUs having sizes of N×N.

FIG. 5 is a diagram illustrating the form of a Transform Unit (TU) thatcan be included in a CU.

A Transform Unit (TU) may have a base unit that is used for a procedure,such as transform, quantization, inverse transform, dequantization,entropy encoding, and entropy decoding, in a CU. A TU may have a squareshape or a rectangular shape.

Among CUs partitioned from the LCU, a CU which is not partitioned intoCUs any further may be partitioned into one or more TUs. Here, thepartition structure of a TU may be a quad-tree structure. For example,as shown in FIG. 5, a single CU 510 may be partitioned one or more timesdepending on the quad-tree structure. By means of this partitioning, thesingle CU 510 may be composed of TUs having various sizes.

In the encoding apparatus 100, a Coding Tree Unit (CTU) having a size of64×64 may be partitioned into multiple smaller CUs by a recursivequad-tree structure. A single CU may be partitioned into four CUs havingthe same size. Each CU may be recursively partitioned, and may have aquad-tree structure.

A CU may have a given depth. When the CU is partitioned, CUs resultingfrom partitioning may have a depth increased from the depth of thepartitioned CU by 1.

For example, the depth of a CU may have a value ranging from 0 to 3. Thesize of the CU may range from a size of 64×64 to a size of 8×8 dependingon the depth of the CU.

By the recursive partitioning of a CU, an optimal partitioning methodthat incurs a minimum rate-distortion cost may be selected.

FIG. 6 is a diagram for explaining an embodiment of an intra-predictionprocess.

Arrows radially extending from the center of the graph in FIG. 6indicate the prediction directions of intra-prediction modes. Further,numbers appearing near the arrows indicate examples of mode valuesassigned to intra-prediction modes or to the prediction directions ofthe intra-prediction modes.

Intra encoding and/or decoding may be performed using reference samplesof blocks neighboring a target block. The neighboring blocks may beneighboring reconstructed blocks. For example, intra encoding and/ordecoding may be performed using the values of reference samples whichare included in each neighboring reconstructed block or the codingparameters of the neighboring reconstructed block.

The encoding apparatus 100 and/or the decoding apparatus 200 maygenerate a prediction block by performing intra prediction on a targetblock based on information about samples in a target image. When intraprediction is performed, the encoding apparatus 100 and/or the decodingapparatus 200 may generate a prediction block for the target block byperforming intra prediction based on information about samples in thetarget image. When intra prediction is performed, the encoding apparatus100 and/or the decoding apparatus 200 may perform directional predictionand/or non-directional prediction based on at least one reconstructedreference sample.

A prediction block may be a block generated as a result of performingintra prediction. A prediction block may correspond to at least one of aCU, a PU, and a TU.

The unit of a prediction block may have a size corresponding to at leastone of a CU, a PU, and a TU. The prediction block may have a squareshape having a size of 2N×2N or N×N. The size of N×N may include sizesof 4×4, 8×8, 16×16, 32×32, 64×64, or the like.

Alternatively, a prediction block may a square block having a size of2×2, 4×4, 8×8, 16×16, 32×32, 64×64 or the like or a rectangular blockhaving a size of 2×8, 4×8, 2×16, 4×16, 8×6, or the like.

Intra prediction may be performed in consideration of theintra-prediction mode for the target block. The number ofintra-prediction modes that the target block can have may be apredefined fixed value, and may be a value determined differentlydepending on the attributes of a prediction block. For example, theattributes of the prediction block may include the size of theprediction block, the type of prediction block, etc.

For example, the number of intra-prediction modes may be fixed at 35regardless of the size of a prediction block. Alternatively, the numberof intra-prediction modes may be, for example, 3, 5, 9, 17, 34, 35, or36.

The intra-prediction modes may be non-directional modes or directionalmodes. For example, the intra-prediction modes may include twonon-directional modes and 33 directional modes, as shown in FIG. 6.

The two non-directional modes may include a DC mode and a planar mode.

The directional modes may be prediction modes having a specificdirection or a specific angle.

The intra-prediction modes may each be represented by at least one of amode number, a mode value, and a mode angle. The number ofintra-prediction modes may be M. The value of M may be 1 or more. Inother words, the number of intra-prediction modes may be M, whichincludes the number of non-directional modes and the number ofdirectional modes.

The number of intra-prediction modes may be fixed to M regardless of thesize of a block. Alternatively, the number of intra-prediction modes maydiffer depending on the size of a block and/or the type of colorcomponent. For example, the number of prediction anodes may differdepending on whether a color component is a luma signal or a chromasignal. For example, the larger the size of the block, the greater thenumber of intra-prediction modes. Alternatively, the number ofintra-prediction modes corresponding to a luma component block may begreater than the number of intra-prediction modes corresponding to achroma component block.

For example, in a vertical mode having a mode value of 26, predictionmay be performed in a vertical direction based on the pixel value of areference sample. For example, in a horizontal mode having a mode valueof 10, prediction may be performed in a horizontal direction based onthe pixel value of a reference sample.

Even in directional modes other than the above-described mode, theencoding apparatus 100 and the decoding apparatus 200 may perform intraprediction on a target unit using reference samples depending on anglescorresponding to the directional modes.

Intra-prediction modes located on a right side with respect to thevertical mode may be referred to as ‘vertical-right modes’.Intra-prediction modes located below the horizontal mode may be referredto as ‘horizontal-below modes’. For example, in FIG. 6, theintra-prediction modes in which a mode value is one of 27, 28, 29, 30,31, 32, 33, and 34 may be vertical-right modes 613. Intra-predictionmodes in which a mode value is one of 2, 3, 4, 5, 6, 7, 8, and 9 may behorizontal-below modes 616.

The non-directional mode may include a DC mode and a planar mode. Forexample, a mode value of the DC mode may be 1. A mode value of theplanar mode may be 0.

The directional mode may include an angular mode. Among the plurality ofthe intra prediction modes, remaining modes except for the DC mode andthe planar mode may be directional modes.

When the intra-prediction mode is a DC mode, a prediction block may begenerated based on the average of pixel values of a plurality ofreference pixels. For example, a value of a pixel of a prediction blockmay be determined based on the average of pixel values of a plurality ofreference pixels.

The number of above-described intra-prediction modes and the mode valuesof respective intra-prediction modes are merely exemplary. The number ofabove-described intra-prediction modes and the mode values of respectiveintra-prediction modes may be defined differently depending on theembodiments, implementation and/or requirements.

In order to perform intra prediction on a target block, the step ofchecking whether samples included in a reconstructed neighboring blockcan be used as reference samples of a target block may be performed.When a sample that cannot be used as a reference sample of the targetblock is present among samples in the neighboring block, a valuegenerated via copying and/or interpolation that uses at least one samplevalue, among the samples included in the reconstructed neighboringblock, may replace the sample value of the sample that cannot be used asthe reference sample. When the value generated via copying and/orinterpolation replaces the sample value of the existing sample, thesample may be used as the reference sample of the target block.

In intra prediction, a filter may be applied to at least one of areference sample and a prediction sample based on at least one of theintra-prediction mode and the size of the target block.

When the intra-prediction mode is a planar mode, a sample value of aprediction target block may be generated using a weighted sum of anabove reference sample of the target block, a left reference sample ofthe target block, an above-right reference sample of the target block,and a below-left reference sample of the target block depending on thelocation of the prediction target sample in the prediction block whenthe prediction block of the target block is generated.

When the intra-prediction mode is a DC mode, the average of referencesamples above the target block and the reference samples to the left ofthe target block may be used when the prediction block of the targetblock is generated.

When the intra-prediction mode is a directional mode, a prediction blockmay be generated using the above reference samples, left referencesamples, above-right reference sample and/or below-left reference sampleof the target block.

In order to generate the above-described prediction sample,real-number-based interpolation may be performed.

The intra-prediction mode of the target block may perform predictionfrom intra prediction of a neighboring block adjacent to the targetblock, and the information used for prediction may beentropy-encoded/decoded.

For example, when the intra-prediction modes of the target block and theneighboring block are identical to each other, it may be signaled, usinga predefined flag, that the intra-prediction modes of the target blockand the neighboring block are identical.

For example, an indicator for indicating an intra-prediction modeidentical to that of the target block, among intra-prediction modes ofmultiple neighboring blocks, may be signaled.

When the intra-prediction modes of the target block and the neighboringblock are different from each other, the intra-prediction modeinformation of the target block may be entropy-encoded/decoded based onthe intra-prediction mode of the neighboring block.

FIG. 7 is a diagram for explaining the locations of reference samplesused in an intra-prediction procedure.

FIG. 7 illustrates the locations of reference samples used for intraprediction of a target block. Referring to FIG. 7, reconstructedreference samples used for intra prediction of the target block mayinclude below-left reference samples 731, left reference samples 733, anabove-left corner reference sample 735, above reference samples 737, andabove-right reference samples 739.

For example, the left reference samples 733 may mean reconstructedreference pixels adjacent to the left side of the target block. Theabove reference samples 737 may mean reconstructed reference pixelsadjacent to the top of the target block. The above-left corner referencesample 735 may mean a reconstructed reference pixel located at theabove-left corner of the target block. The below-left reference samples731 may mean reference samples located below a left sample line composedof the left reference samples 733, among samples located on the sameline as the left sample line. The above-right reference samples 739 maymean reference samples located to the right of an above sample linecomposed of the above reference samples 737, among samples located onthe same line as the above sample line.

When the size of a target block is N×N, the numbers of the below-leftreference samples 731, the left reference samples 733, the abovereference samples 737, and the above-right reference samples 739 mayeach be N.

By performing intra prediction on the target block, a prediction blockmay be generated. The generation of the prediction block may include thedetermination of the values of pixels in the prediction block. The sizesof the target block and the prediction block may be equal.

The reference samples used for intra prediction of the target block mayvary depending on the intra-prediction mode of the target block. Thedirection of the intra-prediction mode may represent a dependencerelationship between the reference samples and the pixels of theprediction block. For example, the value of a specified reference samplemay be used as the values of one or more specified pixels in theprediction block. In this case, the specified reference sample and theone or more specified pixels in the prediction block may be the sampleand pixels which are positioned in a straight line in the direction ofan intra-prediction mode. In other words, the value of the specifiedreference sample may be copied as the value of a pixel located in adirection reverse to the direction of the intra-prediction mode.Alternatively, the value of a pixel in the prediction block may be thevalue of a reference sample located in the direction of theintra-prediction mode with respect to the location of the pixel,

In an example, when the intra-prediction mode of a target block is avertical mode having a mode value of 26, the above reference samples 737may be used for intra prediction. When the intra-prediction mode is thevertical mode, the value of a pixel in the prediction block may be thevalue of a reference sample vertically located above the location of thepixel. Therefore, the above reference samples 737 adjacent to the top ofthe target block may be used for intra prediction. Furthermore, thevalues of pixels in one row of the prediction block may be identical tothose of the above reference samples 737.

In an example, when the intra-prediction mode of a target block is ahorizontal mode having a mode value of 10, the left reference samples733 may be used for intra prediction. When the intra-prediction mode isthe horizontal mode, the value of a pixel in the prediction block may bethe value of a reference sample horizontally located left to thelocation of the pixel. Therefore, the left reference samples 733adjacent to the left of the target block may be used for intraprediction. Furthermore, the values of pixels in one column of theprediction block may be identical to those of the left reference samples733.

In an example, when the mode value of the intra-prediction mode of thecurrent block is 18, at least some of the left reference samples 733,the above-left corner reference sample 735, and at least some of theabove reference samples 737 may be used for intra prediction. When themode value of the intra-prediction mode is 18, the value of a pixel inthe prediction block may be the value of a reference sample diagonallylocated at the above-left corner of the pixel.

Further, At least a part of the above-right reference samples 739 may beused for intra prediction in a case that a intra prediction mode havinga mode value of 27, 28, 29, 30, 31, 32, 33 or 34 is used.

Further, At least a part of the below-left reference samples 731 may beused for intra prediction in a case that a intra prediction mode havinga mode value of 2, 3, 4, 5, 6, 7, 8 or 9 is used.

Further, the above-left corner reference sample 735 may be used forintra prediction in a case that a intra prediction mode of which a modevalue is a value ranging from 11 to 25.

The number of reference samples used to determine the pixel value of onepixel in the prediction block may be either or 2 or more.

As described above, the pixel value of a pixel in the prediction blockmay be determined depending on the location of the pixel and thelocation of a reference sample indicated by the direction of theintra-prediction mode. When the location of the pixel and the locationof the reference sample indicated by the direction of theintra-prediction mode are integer positions, the value of one referencesample indicated by an integer position may be used to determine thepixel value of the pixel in the prediction block.

When the location of the pixel and the location of the reference sampleindicated by the direction of the intra-prediction mode are not integerpositions, an interpolated reference sample based on two referencesamples closest to the location of the reference sample may begenerated. The value of the interpolated reference sample may be used todetermine the pixel value of the pixel in the prediction block. In otherwords, when the location of the pixel in the prediction block and thelocation of the reference sample indicated by the direction of theintra-prediction mode indicate the location between two referencesamples, an interpolated value based on the values of the two samplesmay be generated.

The prediction block generated via prediction may not be identical to anoriginal target block. In other words, there may be a prediction errorwhich is the difference between the target block and the predictionblock, and there may also be a prediction error between the pixel of thetarget block and the pixel of the prediction block.

Hereinafter, the terms “difference”, “error”, and “residual” may be usedto have the same meaning, and may be used interchangeably with eachother.

For example, in the case of directional intra prediction, the longer thedistance between the pixel of the prediction block and the referencesample, the greater the prediction error that may occur. Such aprediction error may result in discontinuity between the generatedprediction block and neighboring blocks.

In order to reduce the prediction error, filtering for the predictionblock may be used. Filtering may be configured to adaptively apply afilter to an area, regarded as having a large prediction error, in theprediction block. For example, the area regarded as having a largeprediction error may be the boundary of the prediction block. Further,an area regarded as having a large prediction error in the predictionblock may differ depending on the intra-prediction mode, and thecharacteristics of filters may also differ depending thereon.

FIG. 8 is a diagram for explaining an embodiment of an inter predictionprocedure.

The rectangles shown in FIG. 8 may represent images (or pictures)Further, in FIG. 8, arrows may represent prediction directions. That is,each image may be encoded and/or decoded depending on the predictiondirection.

Images may be classified into an intra Picture (I picture), aUni-prediction Picture or Predictive Coded Picture (P picture), and aBi-prediction Picture or Bi-predictive Coded Picture (B picture)depending on the encoding type. Each picture may be encoded depending onthe encoding type thereof.

When a target image that is the target to be encoded is an I picture,the target image may be encoded using data contained in the image itselfwithout inter prediction that refers to other images. For example, an Ipicture may be encoded only via intra prediction.

When a target image is a P picture, the target image may be encoded viainter prediction, which uses reference pictures existing in onedirection. Here, the one direction may be a forward direction or abackward direction.

When a target image is a B picture, the image may be encoded via interprediction that uses reference pictures existing in two directions, ormay be encoded via inter prediction that uses reference picturesexisting in one of a forward direction and a backward direction. Here,the two directions may be the forward direction and the backwarddirection.

A P picture and a B picture that are encoded and/or decoded usingreference pictures may be regarded as images in which inter predictionis used.

Below, inter prediction in an inter mode according to an embodiment willbe described in detail.

Inter prediction may be performed using motion information.

In an inter mode, the encoding apparatus 100 may perform interprediction and/or motion compensation on a target block. The decodingapparatus 200 may perform inter prediction and/or motion compensation,corresponding to inter prediction and/or motion compensation performedby the encoding apparatus 100, on a target block.

Motion information of the target block may be individually derived bythe encoding apparatus 100 and the decoding apparatus 200 during theinter prediction. The motion information may be derived using motioninformation of a reconstructed neighboring block, motion information ofa col block, and/or motion information of a block adjacent to the colblock.

For example, the encoding apparatus 100 or the decoding apparatus 200may perform prediction and/or motion compensation by using motioninformation of a spatial candidate and/or a temporal candidate as motioninformation of the target block. The target block may mean a PU and/or aPU partition.

A spatial candidate may be a reconstructed block which is spatiallyadjacent to the target block.

A temporal candidate may be a reconstructed block corresponding to thetarget block in a previously reconstructed co-located picture (colpicture).

In inter prediction, the encoding apparatus 100 and the decodingapparatus 200 may improve encoding efficiency and decoding efficiency byutilizing the motion information of a spatial candidate and/or atemporal candidate. The motion information of a spatial candidate may bereferred to as ‘spatial motion information’. The motion information of atemporal candidate may be referred to as ‘temporal motion information’.

Below, the motion information of a spatial candidate may be the motioninformation of a PU including the spatial candidate. The motioninformation of a temporal candidate may be the motion information of aPU including the temporal candidate. The motion information of acandidate block may be the motion information of a PU including thecandidate block.

Inter prediction may be performed using a reference picture.

The reference picture may be at least one of a picture previous to atarget picture and a picture subsequent to the target picture. Thereference picture may be an image used for the prediction of the targetblock.

In inter prediction, a region in the reference picture may be specifiedby utilizing a reference picture index (or refIdx) for indicating areference picture, a motion vector, which will be described later, etc.Here, the region specified in the reference picture may indicate areference block.

Inter prediction may select a reference picture, and may also select areference block corresponding to the target block from the referencepicture. Further, inter prediction may generate a prediction block forthe target block using the selected reference block.

The motion information may be derived during inter prediction by each ofthe encoding apparatus 100 and the decoding apparatus 200.

A spatial candidate may be a block 1) which is present in a targetpicture, 2) which has been previously reconstructed via encoding and/ordecoding, and 3) which is adjacent to the target block or is located atthe corner of the target block. Here, the “block located at the cornerof the target block” may be either a block vertically adjacent to aneighboring block that is horizontally adjacent to the target block, ora block horizontally adjacent to a neighboring block that is verticallyadjacent to the target block. Further, “block located at the corner ofthe target block” may have the same meaning as “block adjacent to thecorner of the target block”. The meaning of “block located at the cornerof the target block” may be included in the meaning of “block adjacentto the target block”.

For example, a spatial candidate may be a reconstructed block located tothe left of the target block, a reconstructed block located above thetarget block, a reconstructed block located at the below-left corner ofthe target block, a reconstructed block located at the above-rightcorner of the target block, or a reconstructed block located at theabove-left corner of the target block.

Each of the encoding apparatus 100 and the decoding apparatus 200 mayidentify a block present at the location spatially corresponding to thetarget block in a col picture. The location of the target block in thetarget picture and the location of the identified block in the colpicture may correspond to each other.

Each of the encoding apparatus 100 and the decoding apparatus 200 maydetermine a col block present at the predefined relative location forthe identified block to be a temporal candidate. The predefined relativelocation may be a location present inside and/or outside the identifiedblock.

For example, the col block may include a first col block and a secondcol block. When the coordinates of the identified block are (xP, yP) andthe size of the identified block is represented by (nPSW, nPSH), thefirst col block may be a block located at coordinates (xP+nPSW,yP+nPSH). The second col block may be a block located at coordinates(xP+T (nPSW»1), yP (nPSH»1)). The second col block may be selectivelyused when the first col block is unavailable.

The motion vector of the target block may be determined based on themotion vector of the col block. Each of the encoding apparatus 100 andthe decoding apparatus 200 may scale the motion vector of the col block.The scaled motion vector of the col block may be used as the motionvector of the target block. Further, a motion vector for the motioninformation of a temporal candidate stored in a list may be a scaledmotion vector.

The ratio of the motion vector of the target block to the motion vectorof the col block may be identical to the ratio of a first distance to asecond distance. The first distance may be the distance between thereference picture and the target picture of the target block. The seconddistance may be the distance between the reference picture and the colpicture of the col block.

The scheme for deriving motion information may change depending on theinter-prediction mode of a target block. For example, asinter-prediction modes applied for inter prediction, an Advanced MotionVector Predictor (AMVP) mode, a merge mode, a skip mode, a currentpicture reference mode. etc. may be present. The merge mode may also bereferred to as a “motion merge mode”. Individual modes will be describedin detail below.

1) AMVP Mode

When an AMVP mode is used, the encoding apparatus 100 may search aneighboring region of a target block for a similar block. The encodingapparatus 100 may acquire a prediction block by performing prediction onthe target block using motion information of the found similar block.The encoding apparatus 100 may encode a residual block, which is thedifference between the target block and the prediction block.

1-1) Creation of List of Prediction Motion Vector Candidates

When an AMVP mode is used as the prediction mode, each of the encodingapparatus 100 and the decoding apparatus 200 may create a list ofprediction motion vector candidates using the motion vector of a spatialcandidate, the motion vector of a temporal candidate, and a zero vector.The prediction motion vector candidate list may include one or moreprediction motion vector candidates. At least one of the motion vectorof a spatial candidate, the motion vector of a temporal candidate, and azero vector may be determined and used as a prediction motion vectorcandidate.

Hereinafter, the terms “prediction motion vector (candidate)” and“motion vector (candidate)” may be used to have the same meaning, andmay be used interchangeably with each other.

Hereinafter, the terms “prediction motion vector candidate” and “AMVPcandidate” may be used to have the same meaning, and may be usedinterchangeably with each other.

Hereinafter, the terms “prediction motion vector candidate list” and“AMVP candidate list” may be used to have the same meaning, and may beused interchangeably with each other.

Spatial motion candidates may include a reconstructed spatialneighboring block. In other words, the motion vector of thereconstructed neighboring block may be referred to as a “spatialprediction motion vector candidate”.

Temporal motion candidates may include a col block and a block adjacentto the col block. In other words, the motion vector of the col block orthe motion vector of the block adjacent to the col block may be referredto as a “temporal prediction motion vector candidate”.

The zero vector may be a (0, 0) motion vector.

The prediction motion vector candidates may be motion vector predictorsfor predicting a motion vector. Also, in the encoding apparatus 100,each prediction motion vector candidate may be an initial searchlocation for a motion vector.

1-2) Search for Motion Vectors That Use List of Prediction Motion VectorCandidates

The encoding apparatus 100 may determine the motion vector to be used toencode a target block within a search range using a list of predictionmotion vector candidates. Further, the encoding apparatus 100 maydetermine a prediction motion vector candidate to be used as theprediction motion vector of the target block, among prediction motionvector candidates present in the prediction motion vector candidatelist.

The motion vector to be used to encode the target block may be a motionvector that can be encoded at minimum cost.

Further, the encoding apparatus 100 may determine whether to use theAMVP mode to encode the target block.

1-3) Transmission of Inter-Prediction Information

The encoding apparatus 100 may generate a bitstream includinginter-prediction information required for inter prediction. The decodingapparatus 200 may perform inter prediction on the target block using theinter-prediction information of the bitstream.

The inter-prediction information may contain 1) mode informationindicating whether an AMVP mode is used, 2) a prediction motion vectorindex, 3) a Motion Vector Difference (MVD), 4) a reference direction,and 5) a reference picture index.

Hereinafter, the terms “prediction motion vector index” and “AMVP index”may be used to have the same meaning, and may be used interchangeablywith each other. Further, the inter-prediction information may contain aresidual signal.

The decoding apparatus 200 may acquire a prediction motion vector index,an MVD, a reference direction, and a reference picture index from thebitstream through entropy decoding when mode information indicates thatthe AMVP mode is used.

The prediction motion vector index may indicate a prediction motionvector candidate to be used for the prediction of a target block, amongprediction motion vector candidates included in the prediction motionvector candidate list.

1-4) Inter Prediction in AMVP Mode That Uses Inter-PredictionInformation

The decoding apparatus 200 may derive prediction motion vectorcandidates using a prediction motion vector candidate list, and maydetermine the motion information of a target block based on the derivedprediction motion vector candidates.

The decoding apparatus 200 may determine a motion vector candidate forthe target block, among the prediction motion vector candidates includedin the prediction motion vector candidate list, using a predictionmotion vector index. The decoding apparatus 200 may select a predictionmotion vector candidate, indicated by the prediction motion vectorindex, from among prediction motion vector candidates included in theprediction motion vector candidate list, as the prediction motion vectorof the target block.

The motion vector to be actually used for inter prediction of the targetblock may not match the prediction motion vector. In order to indicatethe difference between the motion vector to be actually used for interprediction of the target block and the prediction motion vector, an MVDmay be used. The encoding apparatus 100 may derive a prediction motionvector similar to the motion vector to be actually used for interprediction of the target block so as to use an MVD that is as small aspossible.

An MVD may be the difference between the motion vector of the targetblock and the prediction motion vector. The encoding apparatus 100 maycalculate an MVD and may entropy-encode the MVD.

The MVD may be transmitted from the encoding apparatus 100 to thedecoding apparatus 200 through a bitstream. The decoding apparatus 200may decode the received MVD. The decoding apparatus 200 may derive themotion vector of the target block by summing the decoded MVD and theprediction motion vector. In other words, the motion vector of thetarget block derived by the decoding apparatus 200 may be the sum of theentropy-decoded MVD and the motion vector candidate.

The reference direction may indicate a list of reference pictures to beused for prediction of the target block. For example, the referencedirection may indicate one of a reference picture list L0 and areference picture list L1.

The reference direction merely indicates the reference picture list tobe used for prediction of the target block, and may not mean that thedirections of reference pictures are limited to a forward direction or abackward direction. In other words, each of the reference picture listL0 and the reference picture list L1 may include pictures in a forwarddirection and/or a backward direction.

That the reference direction is unidirectional may mean that a singlereference picture list is used. That the reference direction isbidirectional may mean that two reference picture lists are used. Inother words, the reference direction may indicate one of the case whereonly the reference picture list L0 is used, the case where only thereference picture list L1 is used, and the case where two referencepicture lists are used.

The reference picture index may indicate a reference picture to be usedfor prediction of a target block, among reference pictures in thereference picture list. The reference picture index may beentropy-encoded by the encoding apparatus 100. The entropy-encodedreference picture index may be signaled to the decoding apparatus 200 bythe encoding apparatus 100 through a bitstream.

When two reference picture lists are used to predict the target block, asingle reference picture index and a single motion vector may be usedfor each of the reference picture lists. Further, when two referencepicture lists are used to predict the target block, two predictionblocks may be specified for the target block. For example, the (final)prediction block of the target block may be generated using the averageor weighted sum of the two prediction blocks for the target block.

The motion vector of the target block may be derived by the predictionmotion vector index, the MVD, the reference direction, and the referencepicture index.

The decoding apparatus 200 may generate a prediction block for thetarget block based on the derived motion vector and the referencepicture index. For example, the prediction block may be a referenceblock, indicated by the derived motion vector, in the reference pictureindicated by the reference picture index.

Since the prediction motion vector index and the MVD are encoded withoutthe motion vector itself of the target block being encoded, the numberof bits transmitted from the encoding apparatus 100 to the decodingapparatus 200 may be decreased, and encoding efficiency may be improved.

For the target block, the motion information of reconstructedneighboring blocks may be used. In a specific inter-prediction mode, theencoding apparatus 100 may not separately encode the actual motioninformation of the target block. The motion information of the targetblock is not encoded, and additional information that enables the motioninformation of the target block to be derived using the motioninformation of reconstructed neighboring blocks may be encoded instead.As the additional information is encoded, the number of bits transmittedto the decoding apparatus 200 may be decreased, and encoding efficiencymay be improved.

For example, as inter-prediction modes in which the motion informationof the target block is not directly encoded, there may be a skip modeand/or a merge mode. Here, each of the encoding apparatus 100 and thedecoding apparatus 200 may use an identifier and/or an index thatindicates a unit, the motion information of which is to be used as themotion information of the target unit, among reconstructed neighboringunits.

2) Merge Mode

As a scheme for deriving the motion information of a target block, thereis merging. The term “merging” may mean the merging of the motion ofmultiple blocks, “Merging” may mean that the motion information of oneblock is also applied to other blocks. In other words, a merge mode maybe a mode in which the motion information of the target block is derivedfrom the motion information of a neighboring block.

When a merge mode is used, the encoding apparatus 100 may predict themotion information of a target block using the motion information of aspatial candidate and/or the motion information of a temporal candidate.The spatial candidate may include a reconstructed spatial neighboringblock that is spatially adjacent to the target block. The spatiallyadjacent block may include a left adjacent block and an above adjacentblock. The temporal candidate may include a col block. The terms“spatial candidate” and “spatial merge candidate” may be used to havethe same meaning, and may be used interchangeably with each other. Theterms “temporal candidate” and “temporal merge candidate” may be used tohave the same meaning, and may be used interchangeably with each other.

The encoding apparatus 100 may acquire a prediction block viaprediction. The encoding apparatus 100 may encode a residual block,which is the difference between the target block and the predictionblock.

2-1) Creation of Merge Candidate List

When the merge mode is used, each of the encoding apparatus 100 and thedecoding apparatus 200 may create a merge candidate list using themotion information of a spatial candidate and/or the motion informationof a temporal candidate. The motion information may include 1) a motionvector, 2) a reference picture index, and 3) a reference direction. Thereference direction may be unidirectional or bidirectional.

The merge candidate list may include merge candidates. The mergecandidates may be motion information. In other words, the mergecandidate list may be a list in which pieces of motion information arestored.

The merge candidates may be pieces of motion information of temporalcandidates and/or spatial candidates. Further, the merge candidate listmay include new merge candidates generated by a combination of mergecandidates that are already present in the merge candidate list. Inother words, the merge candidate list may include new motion informationgenerated by a combination of pieces of motion information previouslypresent in the merge candidate list.

The merge candidates may be specific modes deriving inter predictioninformation. The merge candidate may be information indicating aspecific mode deriving inter prediction information. Inter predictioninformation of a target block may be derived according to a specificmode which the merge candidate indicates. Furthermore, the specific modemay include a process of deriving a series of inter predictioninformation. This specific mode may be an inter prediction informationderivation mode or a motion information derivation mode.

The inter prediction information of the target block may be derivedaccording to the mode indicated by the merge candidate selected by themerge index among the merge candidates in the merge candidate list.

For example, the motion information derivation modes in the mergecandidate list may be at least one of 1) motion information derivationmode for a sub-block unit and 2) an affine motion information derivationmode. Furthermore, the merge candidate list may include motioninformation of a zero vector. The zero vector may also be referred to asa “zero-merge candidate”.

In other words, pieces of motion information in the merge candidate listmay be at least one of 1) motion information of a spatial candidate, 2)motion information of a temporal candidate, 3) motion informationgenerated by a combination of pieces of motion information previouslypresent in the merge candidate list, and 4) a zero vector.

Motion information may include 1) a motion vector, 2) a referencepicture index, and 3) a reference direction. The reference direction mayalso be referred to as an “inter-prediction indicator”. The referencedirection may be unidirectional or bidirectional. The unidirectionalreference direction may indicate L0 prediction or L1 prediction.

The merge candidate list may be created before prediction in the mergemode is performed.

The number of merge candidates in the merge candidate list may bepredefined. Each of the encoding apparatus 100 and the decodingapparatus 200 may add merge candidates to the merge candidate listdepending on the predefined scheme and predefined priorities so that themerge candidate list has a predefined number of merge candidates. Themerge candidate list of the encoding apparatus 100 and the mergecandidate list of the decoding apparatus 200 may be made identical toeach other using the predefined scheme and the predefined priorities.

Merging may be applied on a CU basis or a PU basis. When merging isperformed on a CU basis or a PU basis, the encoding apparatus 100 maytransmit a bitstream including predefined information to the decodingapparatus 200. For example, the predefined information may contain 1)information indicating whether to perform merging for individual blockpartitions, and 2) information about a block with which merging is to beperformed, among blocks that are spatial candidates and/or temporalcandidates for the target block.

2-2) Search for Motion Vector That Uses Merge Candidate List

The encoding apparatus 100 may determine merge candidates to be used toencode a target block. For example, the encoding apparatus 100 mayperform prediction on the target block using merge candidates in themerge candidate list, and may generate residual blocks for the mergecandidates. The encoding apparatus 100 may use a merge candidate thatincurs the minimum cost in prediction and in the encoding of residualblocks to encode the target block.

Further, the encoding apparatus 100 may determine whether to use a mergemode to encode the target block.

2-3) Transmission of Inter-Prediction Information

The encoding apparatus 100 may generate a bitstream that includesinter-prediction information required for inter prediction. The encodingapparatus 100 may generate entropy-encoded inter-prediction informationby performing entropy encoding on inter-prediction information, and maytransmit a bitstream including the entropy-encoded inter-predictioninformation to the decoding apparatus 200. Through the bitstream, theentropy-encoded inter-prediction information may be signaled to thedecoding apparatus 200 by the encoding apparatus 100.

The decoding apparatus 200 may perform inter prediction on the targetblock using the inter-prediction information of the bitstream.

The inter-prediction information may contain 1) mode informationindicating whether a merge mode is used and 2) a merge index.

Further, the inter-prediction information may contain a residual signal.

The decoding apparatus 200 may acquire the merge index from thebitstream only when the mode information indicates that the merge modeis used.

The mode information may be a merge flag. The unit of the modeinformation may be a block. Information about the block may include modeinformation, and the mode information may indicate whether a merge modeis applied to the block.

The merge index may indicate a merge candidate to be used for theprediction of the target block, among merge candidates included in themerge candidate list. Alternatively, the merge index may indicate ablock with which the target block is to be merged, among neighboringblocks spatially or temporally adjacent to the target block.

The encoding apparatus 100 may select the merge candidate having thehighest encoding performance from among merge candidates included in amerge candidate list, and may set the value of a merge index so that themerge index indicates the selected merge candidate.

2-4) Inter Prediction of Merge Mode That Uses Inter-PredictionInformation

The decoding apparatus 200 may perform prediction on the target blockusing the merge candidate indicated by the merge index, among mergecandidates included in the merge candidate list.

The motion vector of the target block may be specified by the motionvector, reference picture index, and reference direction of the mergecandidate indicated by the merge index.

3) Skip Mode

A skip mode may be a mode in which the motion information of a spatialcandidate or the motion information of a temporal candidate is appliedto the target block without change. Also, the skip mode may be a mode inwhich a residual signal is not used. In other words, when the skip modeis used, a reconstructed block may be a prediction block.

The difference between the merge mode and the skip mode lies in whetheror not a residual signal is transmitted or used. That is, the skip modemay be similar to the merge mode except that a residual signal is nottransmitted or used.

When the skip mode is used, the encoding apparatus 100 may transmitinformation about a block, the motion information of which is to be usedas the motion information of the target block, among blocks that arespatial candidates or temporal candidates, to the decoding apparatus 200through a bitstream. The encoding apparatus 100 may generateentropy-encoded information by performing entropy encoding on theinformation, and may signal the entropy-encoded information to thedecoding apparatus 200 through a bitstream.

Further, when the skip mode is used, the encoding apparatus 100 may nottransmit other syntax information, such as an MVD, to the decodingapparatus 200. For example, when the skip mode is used, the encodingapparatus 100 may not signal a syntax element related to at least one ofan MVC, a coded block flag, and a transform coefficient level to thedecoding apparatus 200.

3-1) Creation of Merge Candidate List

The skip mode may also use a merge candidate list. In other words, amerge candidate list may be used both in the merge mode and in the skipmode. In this aspect, the merge candidate list may also be referred toas a “skip candidate list” or a “merge/skip candidate list”.

Alternatively, the skip mode may use an additional candidate listdifferent from that of the merge mode. In this case, in the followingdescription, a merge candidate list and a merge candidate may bereplaced with a skip candidate list and a skip candidate, respectively.

The merge candidate list may be created before prediction in the skipmode is performed.

3-2) Search for Motion Vector That Uses Merge Candidate List

The encoding apparatus 100 may determine the merge candidates to be usedto encode a target block. For example, the encoding apparatus 100 mayperform prediction on the target block using the merge candidates in amerge candidate list. The encoding apparatus 100 may use a mergecandidate that incurs the minimum cost in prediction to encode thetarget block.

Further, the encoding apparatus 100 may determine whether to use a skipmode to encode the target block.

3-3) Transmission of Inter-Prediction Information

The encoding apparatus 100 may generate a bitstream that includesinter-prediction information required for inter prediction. The decodingapparatus 200 may perform inter prediction on the target block using theinter-prediction information of the bitstream.

The inter-prediction information may include 1) mode informationindicating whether a skip mode is used, and 2) a skip index.

The skip index may be identical to the above-described merge index.

When the skip mode is used, the target block may be encoded withoutusing a residual signal. The inter-prediction information may notcontain a residual signal. Alternatively, the bitstream may not includea residual signal.

The decoding apparatus 200 may acquire a skip index from the bitstreamonly when the mode information indicates that the skip mode is used. Asdescribed above, a merge index and a skip index may be identical to eachother. The decoding apparatus 200 may acquire the skip index from thebitstream only when the mode information indicates that the merge modeor the skip mode is used.

The skip index may indicate the merge candidate to be used for theprediction of the target block, among the merge candidates included inthe merge candidate list.

3-4) Inter Prediction in Skip Mode That Uses Inter-PredictionInformation

The decoding apparatus 200 may perform prediction on the target blockusing a merge candidate indicated by a skip index, among the mergecandidates included in a merge candidate list.

The motion vector of the target block may be specified by the motionvector, reference picture index, and reference direction of the mergecandidate indicated by the skip index.

4) Current Picture Reference Mode

The current picture reference mode may denote a prediction mode thatuses a previously reconstructed region in a target picture to which atarget block belongs.

A vector for specifying the previously reconstructed region may bedefined. Whether the target block has been encoded in the currentpicture reference mode may be determined using the reference pictureindex of the target block.

A flag or index indicating whether the target block is a block encodedin the current picture reference mode may be signaled by the encodingapparatus 100 to the decoding apparatus 200. Alternatively, whether thetarget block is a block encoded in the current picture reference modemay be inferred through the reference picture index of the target block.

When the target block is encoded in the current picture reference mode,the target picture may be added to a fixed location or an arbitrarylocation in a reference picture list for the target block.

For example, the fixed location may be either a location where thereference picture index is 0 or the last location.

When the target picture is added to an arbitrary location in thereference picture list, an additional reference picture index indicatingsuch an arbitrary location may be signaled by the encoding apparatus 100to the decoding apparatus 200.

In the above-described AMVP mode, merge mode, and skip mode, motioninformation to be used for the prediction of a target block may bespecified, among pieces of motion information in the list, using theindex of the list.

In order to improve encoding efficiency, the encoding apparatus 100 maysignal only the index of an element that incurs the minimum cost ininter prediction of the target block, among elements in the list. Theencoding apparatus 100 may encode the index, and may signal the encodedindex.

Therefore, the above-described lists (i.e. the prediction motion vectorcandidate list and the merge candidate list) must be able to be derivedby the encoding apparatus 100 and the decoding apparatus 200 using thesame scheme based on the same data. Here, the same data may include areconstructed picture and a reconstructed block. Further, in order tospecify an element using an index, the order of the elements in the listmust be fixed.

FIG. 9 illustrates spatial candidates according to an embodiment.

In FIG. 9, the locations of spatial candidates are illustrated.

The large block in the center of the drawing may denote a target block.Five small blocks may denote spatial candidates.

The coordinates of the target block may be (xP, yP), and the size of thetarget block may be represented by (nPSW, nPSH).

Spatial candidate A₀ may be a block adjacent to the below-left corner ofthe target block. Ac may be a block that occupies pixels located atcoordinates (xP−1, yP+nPSH+1).

Spatial candidate A₁ may be a block adjacent to the left of the targetblock, A₁ may be a lowermost block, among blocks adjacent to the left ofthe target block. Alternatively, A₁ may be a block adjacent to the topof A₀. A₁ may be a block that occupies pixels located at coordinates(xP−1, yP+nPSH).

Spatial candidate B₀ may be a block adjacent to the above-right cornerof the target block. B₀ may be a block that occupies pixels located atcoordinates (xP+nPSW+1, yP−1).

Spatial candidate B₁ may be a block adjacent to the top of the targetblock. B₁ may be a rightmost block, among blocks adjacent to the top ofthe target block. Alternatively, B₁ may be a block adjacent to the leftof B₀. B₁ may be a block that occupies pixels located at coordinates(xP+nPSW, yP−1).

Spatial candidate B₂ may be a block adjacent to the above-left corner ofthe target block. B₂ may be a block that occupies pixels located atcoordinates (xP−1, yP−1).

Determination of Availability of Spatial Candidate and TemporalCandidate

In order to include the motion information of a spatial candidate or themotion information of a temporal candidate in a list, it must bedetermined whether the motion information of the spatial candidate orthe motion information of the temporal candidate is available.

Hereinafter, a candidate block may include a spatial candidate and atemporal candidate,

For example, the determination may be performed by sequentially applyingthe following steps 1) to 4).

Step 1) When a PU including a candidate block is out of the boundary ofa picture, the availability of the candidate block may be set to“false”. The expression “availability is set to false” may have the samemeaning as “set to be unavailable”.

Step 2) When a PU including a candidate block is out of the boundary ofa slice, the availability of the candidate block may be set to “false”.When the target block and the candidate block are located in differentslices, the availability of the candidate block may be set to “false”.

Step 3) When a PU including a candidate block is out of the boundary ofa tile, the availability of the candidate block may be set to “false”.When the target block and the candidate block are located in differenttiles, the availability of the candidate block may be set to “false”.

Step 4) When the prediction mode of a PU including a candidate block isan intra-prediction mode, the availability of the candidate block may beset to “false”. When a PU including a candidate block does not use interprediction, the availability of the candidate block may be set to“false”.

FIG. 10 illustrates the order of addition of motion information ofspatial candidates to a merge list according to an embodiment.

As shown in FIG. 10, when pieces of motion information of spatialcandidates are added to a merge list, the order of A₁, B₁, B₀, A₀, andB₂ may be used. That is, pieces of motion information of availablespatial candidates may be added to the merge list in the order of A₁,B₁, B₀, A₀, and B₂.

Method for Deriving Merge List in Merge Mode and Skip Mode

As described above, the maximum number of merge candidates in the mergelist may be set. The set maximum number is indicated by “N”. The setnumber may be transmitted from the encoding apparatus 100 to thedecoding apparatus 200. The slice header of a slice may include N. Inother words, the maximum number of merge candidates in the merge listfor the target block of the slice may be set by the slice header. Forexample, the value of N may be basically 5.

Pieces of motion information (i.e., merge candidates) nay be added tothe merge list in the order of the following steps 1) to 4).

Step 1) Among spatial candidates, available spatial candidates may beadded to the merge list. Pieces of motion information of the availablespatial candidates may be added to the merge list in the orderillustrated in FIG. 10. Here, when the motion information of anavailable spatial candidate overlaps other motion information alreadypresent in the merge list, the motion information may not be added tothe merge list. The operation of checking whether the correspondingmotion information overlaps other motion information present in the listmay be referred to in brief as an “overlap check”.

The maximum number of pieces of motion information that are added may beN.

Step 2) When the number of pieces of motion information in the mergelist is less than N and a temporal candidate is available, the motioninformation of the temporal candidate may be added to the merge list.Here, when the motion information of the available temporal candidateoverlaps other motion information already present in the merge list, themotion information may not be added to the merge list.

Step 3) When the number of pieces of motion information in the mergelist is less than N and the type of a target slice is “B”, combinedmotion information generated by combined bidirectional prediction(bi-prediction) may be added to the merge list.

The target slice may be a slice including a target block.

The combined motion information may be a combination of L0 motioninformation and L1 motion information. L0 motion information may bemotion information that refers only to a reference picture list L0. L1motion information may be motion information that refers only to areference picture list L1.

In the merge list, one or more pieces of L0 motion information may bepresent. Further, in the merge list, one or more pieces of L1 motioninformation may be present.

The combined motion information may include one or more pieces ofcombined motion information. When the combined motion information isgenerated, L0 motion information and L1 motion information, which are tobe used for generation, among the one or more pieces of L0 motioninformation and the one or more pieces of L1 motion information, may bepredefined. One or more pieces of combined motion information may begenerated in a predefined order via combined bidirectional prediction,which uses a pair of different pieces of motion information in the mergelist. One of the pair of different pieces of motion information may beL0 motion information and the other of the pair may be L1 motioninformation.

For example, combined motion information that is added with the highestpriority may be a combination of L0 motion information having a mergeindex of 0 and L1 motion information having a merge index of 1. Whenmotion information having a merge index of 0 is not L0 motioninformation or when motion information having a merge index of 1 is notL1 motion information, the combined motion information may be neithergenerated nor added. Next, the combined motion information that is addedwith the next priority may be a combination of L0 motion information,having a merge index of 1, and L1 motion information, having a mergeindex of 0. Subsequent detailed combinations may conform to othercombinations of video encoding/decoding fields.

Here, when the combined motion information overlaps other motioninformation already present in the merge list, the combined motioninformation may not be added to the merge list.

Step 4) When the number of pieces of motion information in the mergelist is less than N, motion information of a zero vector may be added tothe merge list.

The zero-vector motion information may be motion information for whichthe motion vector is a zero vector.

The number of pieces of zero-vector motion information may be one ormore. The reference picture indices of one or more pieces of zero-vectormotion information may be different from each other. For example, thevalue of the reference picture index of first zero-vector motioninformation may be 0. The value of the reference picture index of secondzero-vector motion information may be 1.

The number of pieces of zero-vector motion information may be identicalto the number of reference pictures in the reference picture list.

The reference direction of zero-vector motion information may bebidirectional. Both of the motion vectors may be zero vectors. Thenumber of pieces of zero-vector motion information may be the smallerone of the number of reference pictures in the reference picture list L0and the number of reference pictures in the reference picture list L1.Alternatively, when the number of reference pictures in the referencepicture list L0 and the number of reference pictures in the referencepicture list L1 are different from each other, a reference directionthat is unidirectional may be used for a reference picture index thatmay be applied only to a single reference picture list.

The encoding apparatus 100 and/or the decoding apparatus 200 maysequentially add the zero-vector motion information to the merge listwhile changing the reference picture index.

When zero-vector motion information overlaps other motion informationalready present in the merge list, the zero-vector motion informationmay not be added to the merge list.

The order of the above-described steps 1) to 4) is merely exemplary, andmay be changed. Further, some of the above steps may be omitteddepending on predefined conditions.

Method for Deriving Prediction Motion Vector Candidate List in AMVP Mode

The maximum number of prediction motion vector candidates in aprediction motion vector candidate list may be predefined. Thepredefined maximum number is indicated by N. For example, the predefinedmaximum number may be 2.

Pieces of motion information (i.e. prediction motion vector candidates)may be added to the prediction motion vector candidate list in the orderof the following steps 1) to 3).

Step 1) Available spatial candidates, among spatial candidates, may beadded to the prediction motion vector candidate list. The spatialcandidates may include a first spatial candidate and a second spatialcandidate.

The first spatial candidate may be one of A₀, A₁, scaled A₀, and scaledA₁. The second spatial candidate may be one of B₀, B₁, B₂, scaled B₀,scaled B₁, and scaled B₂.

Pieces of motion information of available spatial candidates may beadded to the prediction motion vector candidate list in the order of thefirst spatial candidate and the second spatial candidate. In this case,when the motion information of an available spatial candidate overlapsother motion information already present in the prediction motion vectorcandidate list, the motion information may not be added to theprediction motion vector candidate list. In other words, when the valueof N is 2, if the motion information of a second spatial candidate isidentical to the motion information of a first spatial candidate, themotion information of the second spatial candidate may not be added tothe prediction motion vector candidate list.

The maximum number of pieces of motion information that are added may beN.

Step 2) When the number of pieces of motion information in theprediction motion vector candidate list is less than N and a temporalcandidate is available, the motion information of the temporal candidatemay be added to the prediction motion vector candidate list. In thiscase, when the motion information of the available temporal candidateoverlaps other motion information already present in the predictionmotion vector candidate list, the motion information may not be added tothe prediction motion vector candidate list.

Step 3) When the number of pieces of motion information in theprediction motion vector candidate list is less than N, zero-vectormotion information may be added to the prediction motion vectorcandidate list.

The zero-vector motion information may include one or more pieces ofzero-vector motion information. The reference picture indices of the oneor more pieces of zero-vector motion information may be different fromeach other.

The encoding apparatus 100 and/or the decoding apparatus 200 maysequentially add pieces of zero-vector motion information to theprediction motion vector candidate list while changing the referencepicture index.

When zero-vector motion information overlaps other motion informationalready present in the prediction motion vector candidate list, thezero-vector motion information may not be added to the prediction motionvector candidate list.

The description of the zero-vector motion information, made above inconnection with the merge list, may also be applied to zero-vectormotion information. A repeated description thereof will be omitted.

The order of the above-described steps 1) to 3) is merely exemplary, andmay be changed. Further, some of the steps may be omitted depending onpredefined conditions.

FIG. 11 illustrates a transform and quantization process according to anexample.

As illustrated in FIG. 11, quantized levels may be generated byperforming a transform and/or quantization process on a residual signal.

A residual signal may be generated as the difference between an originalblock and a prediction block. Here, the prediction block may be a blockgenerated via intra prediction or inter prediction.

The transform may include at least one of a primary transform and asecondary transform. A transform coefficient may be generated byperforming the primary transform on the residual signal, and a secondarytransform coefficient may be generated by performing the secondarytransform on the transform coefficient.

The primary transform may be performed using at least one of predefinedmultiple transform methods. For example, the predefined multipletransform methods may include a Discrete Cosine Transform (DCT), aDiscrete Sine Transform (DST), a Karhunen-Loeve Transform (KLT), etc.

The secondary transform may be performed on the transform coefficientgenerated by performing the primary transform.

Transform methods applied to the primary transform and/or the secondarytransform may be determined based on at least one of coding parametersfor a target block and/or a neighboring block. Alternatively, transforminformation indicating transform methods may be signaled by the encodingapparatus to the decoding apparatus 200.

The quantized levels may be generated by performing quantization on theresult, generated by performing the primary transform and/or thesecondary transform, or on the residual signal.

The quantized levels may be scanned based on at least one of up-rightdiagonal scanning, vertical scanning, and horizontal scanning, dependingon at least one of an intra-prediction mode, a block size, and a blockform.

For example, coefficients may be changed to 1D vector forms by scanningcoefficients of blocks using up-right diagonal scanning. Alternatively,depending on the size of a transform block and/or an intra-predictionmode, vertical scanning, which scans 2D block-format coefficients in acolumn direction, or horizontal scanning, which scans 2D block-formatcoefficients in a row direction, may be used instead of the up-rightdiagonal scanning.

The scanned quantized levels may be entropy-encoded, and a bitstream mayinclude the entropy-encoded quantized levels.

The decoding apparatus 200 may generate quantized levels via entropydecoding on the bitstream. The quantized levels may be aligned in theform of a 2D block via inverse scanning. Here, as the method of inversescanning, at least one of up-right diagonal scanning, vertical scanning,and horizontal scanning may be performed.

Dequantization may be performed on the quantized levels. A secondaryinverse transform may be performed on the result generated by performingdequantization depending on whether to perform the secondary inversetransform. Further, a primary inverse transform may be performed on theresult generated by performing the secondary inverse transform dependingon whether the primary inverse transform is to be performed. Areconstructed residual signal may be generated by performing the primaryinverse transform on the result generated by performing the secondaryinverse transform.

FIG. 12 is a configuration diagram of an encoding apparatus according toan embodiment.

An encoding apparatus 1200 may correspond to the above-describedencoding apparatus 100.

The encoding apparatus 1200 may include a processing unit 1210, memory1230, a user interface (UI) input device 1250, a UI output device 1260,and storage 1240, which communicate with each other through a bus 1290.The encoding apparatus 1200 may further include a communication unit1220 coupled to a network 1299.

The processing unit 1210 may be a Central Processing Unit (CPU) or asemiconductor device for executing processing instructions stored in thememory 1230 or the storage 1240. The processing unit 1210 may be atleast one hardware processor.

The processing unit 1210 may generate and process signals, data orinformation that are input to the encoding apparatus 1200, are outputfrom the encoding apparatus 1200, or are used in the encoding apparatus1200, and may perform examination, comparison, determination, etc.related to the signals, data or information. In other words, inembodiments, the generation and processing of data or information andexamination, comparison and determination related to data, orinformation may be performed by the processing unit 1210.

The processing unit 1210 may include an inter-prediction unit 110, anintra-prediction unit 120, a switch 115, a subtractor 125, a transformunit 130, a quantization unit 140, an entropy encoding unit 150, adequantization unit 160, an inverse transform unit 170, an adder 175, afilter unit 180, and a reference picture buffer 190.

At least some of the inter-prediction unit 110, the intra-predictionunit 120, the switch 115, the subtractor 125, the transform unit 130,the quantization unit 140, the entropy encoding unit 150, thedequantization unit 160, the inverse transform unit 170, the adder 175,the filter unit 180, and the reference picture buffer 190 may be programmodules, and may communicate with an external device or system. Theprogram modules may be included in the encoding apparatus 1200 in theform of an operating system, an application program module, or otherprogram modules.

The program modules may be physically stored in various types ofwell-known storage devices. Further, at least some of the programmodules may also be stored in a remote storage device that is capable ofcommunicating with the encoding apparatus 1200.

The program modules may include, but are not limited to, a routine, asubroutine, a program, an object, a component, and a data structure forperforming functions or operations according to an embodiment or forimplementing abstract data types according to an embodiment.

The program modules may be implemented using instructions or codeexecuted by at least one processor of the encoding apparatus 1200.

The processing unit 1210 may execute instructions or code in theinter-prediction unit 110, the intra-prediction unit 120, the switch115, the subtractor 125, the transform unit 130, the quantization unit140, the entropy encoding unit 150, the dequantization unit 160, theinverse transform unit 170, the adder 175, the filter unit 180, and thereference picture buffer 190.

A storage unit may denote the memory 1230 and/or the storage 1240. Eachof the memory 1230 and the storage 1240 may be any of various types ofvolatile or nonvolatile storage media. For example, the memory 1230 mayinclude at least one of Read-Only Memory (ROM) 1231 and Random AccessMemory (RAM) 1232.

The storage unit may store data or information used for the operation ofthe encoding apparatus 1200, in an embodiment, the data or informationof the encoding apparatus 1200 may be stored in the storage unit.

For example, the storage unit may store pictures, blocks, lists, motioninformation, inter-prediction information, bitstreams, etc.

The encoding apparatus 1200 may be implemented in a computer systemincluding a computer-readable storage medium.

The storage medium may store at least one module required for theoperation of the encoding apparatus 1200. The memory 1230 may store atleast one module, and may be configured such that the at least onemodule is executed by the processing unit 1210.

Functions related to communication of the data or information of theencoding apparatus 1200 may be performed through the communication unit1220.

For example, the communication unit 1220 may transmit a bitstream to adecoding apparatus 1300, which will be described later.

FIG. 13 is a configuration diagram of a decoding apparatus according toan embodiment.

The decoding apparatus 1300 may correspond to the above-describeddecoding apparatus 200.

The decoding apparatus 1300 may include a processing unit 1310, memory1330, a user interface (UI) input device 1350, a UI output device 1360,and storage 1340, which communicate with each other through a bus 1390.The decoding apparatus 1300 may further include a communication unit1320 coupled to a network 1399.

The processing unit 1310 may be a Central Processing Unit (CPU) or asemiconductor device for executing processing instructions stored in thememory 1330 or the storage 1340. The processing unit 1310 may be atleast one hardware processor.

The processing unit 1310 may generate and process signals, data orinformation that are input to the decoding apparatus 1300, are outputfrom the decoding apparatus 1300, or are used in the decoding apparatus1300, and may perform examination, comparison, determination, etc.related to the signals, data or information. In other words, inembodiments, the generation and processing of data or information andexamination, comparison and determination related to data or informationmay be performed by the processing unit 1310.

The processing unit 1310 may include an entropy decoding unit 210, adequantization unit 220, an inverse transform unit 230, anintra-prediction unit 240, an inter-prediction unit 250, an adder 255, afilter unit 260, and a reference picture buffer 270.

At least some of the entropy decoding unit 210, the dequantization unit220, the inverse transform unit 230, the intra-prediction unit 240, theinter-prediction unit 250, the adder 255, the filter unit 260, and thereference picture buffer 270 of the decoding apparatus 200 may beprogram modules, and may communicate with an external device or system.The program modules may be included in the decoding apparatus 1300 inthe form of an operating system, an application program module, or otherprogram modules.

The program modules may be physically stored in various types ofwell-known storage devices. Further, at least some of the programmodules may also be stored in a remote storage device that is capable ofcommunicating with the decoding apparatus 1300.

The program modules may include, but are not limited to, a routine, asubroutine, a program, an object, a component, and a data structure forperforming functions or operations according to an embodiment or forimplementing abstract data types according to an embodiment.

The program modules may be implemented using instructions or codeexecuted by at least one processor of the decoding apparatus 1300.

The processing unit 1310 may execute instructions or code in the entropydecoding unit 210, the dequantization unit 220, the inverse transformunit 230, the intra-prediction unit 240, the inter-prediction unit 250,the adder 255, the filter unit 260, and the reference picture buffer270.

A storage unit may denote the memory 1330 and/or the storage 1340. Eachof the memory 1330 and the storage 1340 may be any of various types ofvolatile or nonvolatile storage media. For example, the memory 1330 mayinclude at least one of ROM 1331 and RAM 1332.

The storage unit may store data or information used for the operation ofthe decoding apparatus 1300. In an embodiment, the data or informationof the decoding apparatus 1300 may be stored in the storage unit.

For example, the storage unit may store pictures, blocks, lists, motioninformation, inter-prediction information, bitstreams, etc.

The decoding apparatus 1300 may be implemented in a computer systemincluding a computer-readable storage medium.

The storage medium may store at least one module required for theoperation of the decoding apparatus 1300. The memory 1330 may store atleast one module, and may be configured such that the at least onemodule is executed by the processing unit 1310.

Functions related to communication of the data or information of thedecoding apparatus 1300 may be performed through the communication unit1320.

For example, the communication unit 1320 may receive a bitstream fromthe encoding apparatus 1200.

In the following embodiments, in encoding and decoding using interprediction, a method for deriving inter-prediction information of atarget block using inter-prediction information of a neighbor block willbe described.

In encoding and decoding using inter prediction, inter-predictioninformation of the target block in a target picture may be searched forin a previously encoded and/or decoded picture so as to remove temporalredundancy from a video.

As the inter-prediction information of the target block is derived usingthe inter-prediction information of the neighbor block, the amount ofinformation required for inter prediction may be reduced. Here, theamount of information may be the number of bits.

As the method for deriving the inter-prediction information of thetarget block using the inter-prediction information of a neighbor block,an AMVP mode and a merge mode may be used. In the AMVP mode and themerge mode, an AMVP candidate list and a merge candidate list may beindividually configured using temporally adjacent neighbor blocks andspatially adjacent neighbor blocks. Each candidate in such a list may bethe inter-prediction information or a portion of the inter-predictioninformation.

In the configuration of the lists, the lists may be filled withinter-prediction information of available neighbor blocks as candidates.

When there is no inter-prediction information of a neighbor block orwhen inter-prediction information of a neighbor block cannot be used,the inter-prediction information of the neighbor block cannot be used asa candidate.

The maximum number of candidates in each list may be predefined. Whenpieces of inter-prediction information of available neighbor blockscannot fill the predefined maximum number of candidates in the list,zero-vector motion information may be added to the list.

As the correlation between the candidate in the list, that is,inter-prediction information, and the inter-prediction information ofthe target block is higher, encoding performance may be improved.

In contrast, for candidates having a low correlation with theinter-prediction information of the target block, for example,zero-vector motion information, the number of bits to be signaled may beincreased upon deriving inter-prediction information. As the number ofbits that are signaled is increased, encoding performance may bedeteriorated.

In an embodiment, for a target block having no inter-predictioninformation, the encoding apparatus 1200 and the decoding apparatus 1300may generate inter-prediction information for the target block using theinter-prediction information of a neighbor block, and may add thegenerated inter-prediction information as a candidate to thecorresponding list.

In an embodiment, inter-prediction information having a highcorrelation, rather than inter-prediction information having a lowcorrelation, may be added as a, candidate to the list. As theinter-prediction information having a high correlation is added as thecandidate to the list, encoding efficiency may be increased.

In an embodiment, each of the encoding apparatus 1200 and the decodingapparatus 1300 may configure a list for the target block using multiplepieces of inter-prediction information of multiple neighbor blocks. Themultiple neighbor blocks may include temporal neighbor blocks andspatial neighbor blocks. Each of the encoding apparatus 1200 and thedecoding apparatus 1300 may add inter-prediction information having ahigher correlation with the inter-prediction information of the targetblock to the list using the multiple pieces of inter-predictioninformation of the multiple neighbor blocks. By the use and addition ofinter-prediction information, the number of bits for an index or thelike indicating inter-prediction information may be decreased, andencoding performance may be improved.

In an embodiment, when there is no inter-prediction information of thetarget block, each of the encoding apparatus 1200 and the decodingapparatus 1300 may generate inter-prediction information of the targetblock by combining pieces of inter-prediction information of theneighbor blocks of the target block. Each of the encoding apparatus 1200and the decoding apparatus 1300 may add the generated inter-predictioninformation as a candidate to the list. Instead of inter-predictioninformation having a low correlation with the inter-predictioninformation of the target block, for example, zero-vector motioninformation, inter-prediction information having a high correlation withthe inter-prediction information of the target block is added as acandidate to the list, thus enabling more efficient encoding to beperformed in the derivation of inter-prediction information.

During a procedure for recursively splitting a CU, the CU may be splitinto four square blocks of the same size or two blocks of the same size.When the CU is split into two partition blocks, the CU may behorizontally or vertically split. Alternatively, the CU may be splitinto three partition blocks, and may be horizontally or verticallysplit. For example, when the CU is vertically split, the ratio of thewidths of partition blocks generated from splitting may be 1:2:1.Similarly, when the CU is horizontally split, the ratio of the heightsof the partition blocks may be 1:2:1.

Splitting of a block in inter prediction may represent that the encodingefficiency that is obtained when inter prediction is performed usingpieces of motion information of respective partition blocks generatedfrom splitting is higher than the encoding efficiency that is obtainedwhen inter prediction is performed using one piece of motion informationof an unsplit block. In other words, when a block is split, there is astrong possibility that two or four partition blocks will have differentpieces of motion information.

When the target block is a block split from an upper block, the motioninformation of another partition block in the upper block may be usedwhen motion information of a spatial neighbor block in a merge mode isderived for the target block. In other words, the motion information ofthe target block may be derived in the same manner as the motioninformation of the other partition block. In this case, (even ifpartition blocks are generated by splitting from the upper block,) twopartition blocks have the same motion information, and thus encodingperformance may be decreased.

Each of the encoding apparatus 1200 and the decoding apparatus 1300 mayassign a smaller number of bits to a candidate having higher priority,among the candidates in the list. The assigned bits may be the value ofan index indicating the corresponding candidate. In other words, anindex indicating a candidate having higher priority may be signaledusing a smaller number of bits than that of an index indicating acandidate having lower priority.

Each of the encoding apparatus 1200 and the decoding apparatus 1300 maybe configured to assign higher priority to a candidate expected orestimated to have higher encoding performance upon configuring the list.

Here, the assignment of higher priority may mean that 1) a smallernumber of bits are assigned, 2) a smaller index is allocated, or 3) acandidate is included in the list with higher priority to precede othercandidates in the list.

Also, each of the encoding apparatus 1200 and the decoding apparatus1300 may be configured to assign lower priority to a candidate expectedor estimated to have lower encoding performance upon configuring thelist.

Here, the assignment of lower priority may mean that 1) a larger numberof bits are assigned, 2) a larger index is allocated, 3) a candidate isincluded in the list with lower priority to follow other candidates inthe list, or 4) a candidate is not included in the list. By means ofsuch list configuration, encoding performance may be improved.

When a list is configured using the motion information of a spatialneighbor block for a partition CU, each of the encoding apparatus 1200and the decoding apparatus 1300 may include the motion information ofthe spatial neighbor block in the list with lower priority if thespatial neighbor block is a block split from an upper CU including thepartition CU. Alternatively, the encoding apparatus 1200 may not includethe motion information of the spatial neighbor block in the list if thespatial neighbor block is a block split from the upper CU including thepartition CU.

In other words, each of the encoding apparatus 1200 and the decodingapparatus 1300 may not include motion information that is highly likelyto have low encoding performance in the list, and may assign lowerpriority to motion information that is highly likely to have lowencoding performance, By means of such exclusion and assignment, each ofthe encoding apparatus 1200 and the decoding apparatus 1300 preventsmotion information expected or estimated to have low encodingperformance from being selected or decreases the possibility of suchmotion information being selected, thus improving encoding performance.

FIG. 14 is a flowchart of an inter-prediction method according to anembodiment.

The inter-prediction method may be performed by the encoding apparatus1200 and/or the decoding apparatus 1300.

For example, the encoding apparatus 1200 may perform theinter-prediction method according to the embodiment so as to compare theefficiencies of multiple prediction methods for a target block, and mayperform the inter-prediction method according to the embodiment so as togenerate a reconstructed block for the target block.

The target block may be any one of the above-described various blocks.For example, the target block may be a Coding Unit (CU), a PredictionUnit (PU) or a Transform Unit (TU).

For example, the decoding apparatus 1300 may perform theinter-prediction method according to the embodiment so as to generate areconstructed block for the target block.

Below, a processing unit may be the processing unit 1210 of the encodingapparatus 1200 and/or the processing unit 1310 of the decoding apparatus1300.

At step 1410, the processing unit may derive inter-predictioninformation for the target block.

The inter-prediction information may include 1) a motion vector,reference picture list, 3) a reference picture index, 4) a merge flag,5) a merge index, 6) an Advanced Motion Vector Prediction (AMVP) index,7) an illumination compensation (IC) flag, and 8) an Overlapped BlockMotion Compensation (OBMC) flag.

The IC flag may be a flag indicating whether IC is to be applied.

The OBMC flag may be a flag indicating whether OBMC is to be applied.

The processing unit may derive inter-prediction information using atleast one method.

The at least one method may include 1) a merge mode, 2) an AMVP mode, 3)a method for deriving inter-prediction information on a sub-block basis,and 4) a method for deriving inter-prediction information in thedecoding apparatus 1300.

The processing unit may derive inter-prediction information using atleast one piece of information.

The at least one piece of information may include 1) inter-predictioninformation of a spatial neighbor block, 2) inter-prediction informationof a temporal neighbor block, 3) combined inter-prediction information,4) a uniform candidate list, 5) an adaptive candidate list depending ona block shape, and 6) an adaptive candidate list depending on ablock-splitting state.

At step 1420, the processing unit may perform inter prediction for thetarget block using the derived inter-prediction information.

Inter prediction may include motion compensation and/or motioncorrection.

The processing unit may perform inter prediction using at least one ofcompensation and/or correction.

The at least one of compensation and/or correction may include 1) motioncompensation, 2) IC, 3) OBMC, 4) Bidirectional Optical flow (BIO), 5)affine space motion compensation, and 6) motion vector correction in thedecoding apparatus 1300.

Derivation of Inter-Prediction Information Using Merge Mode

The processing unit may derive inter-prediction information using amerge mode. In an embodiment, the merge mode may be replaced with anAMVP mode or a specific inter-prediction mode that uses a list or thelike. In other words, the derivation of inter-prediction informationusing the merge mode, described in the embodiment, may also be appliedto the derivation of inter-prediction information that uses the AMVPmode or the specific inter-prediction mode.

The processing unit may configure a merge candidate list. The number ofmerge candidates in the merge candidate list may be N. N may be apositive integer. For example, a merge candidate may be inter-predictioninformation, and may include a motion vector and a reference picturelist.

The processing unit may configure the merge candidate list using one ormore of inter-prediction information of a spatial neighbor block,inter-prediction information of a temporal neighbor block, and combinedinter-prediction information. Here, the processing unit may add thepieces of inter-prediction information to the merge candidate list in aspecific sequence.

The processing unit may add the pieces of inter-prediction informationof neighbor blocks as merge candidates to the merge candidate list whenthe merge candidate list is configured. Here, the processing unit mayadd the pieces of inter-prediction information of neighbor blocks to themerge candidate list in the specific sequence of the neighbor blocks.The processing unit may not add the inter-prediction information of aneighbor block to the merge candidate list 1) when inter-predictioninformation of the neighbor block is not present or 2) wheninter-prediction information of the neighbor block is identical tointer-prediction information present in the merge candidate list (i.e.,when the inter-prediction information of the neighbor block is alreadyincluded in the merge candidate list). In other words, when pieces ofinter-prediction information of two neighbor blocks are identical toeach other, inter-prediction information of the neighbor block havingthe lower priority may not be added to the merge candidate list.

When inter-prediction information of one of neighbor blocks is not addedto the merge candidate list, the processing unit may add combinedinter-prediction information, instead of the inter-predictioninformation that is not added, to the merge candidate list. For example,when inter-prediction information of a specific neighbor block is notpresent or when the inter-prediction information of the specificneighbor block is identical to inter-prediction information in the mergecandidate list, the processing unit may derive combined inter-predictioninformation for the specific neighbor block, and may add the derivedcombined inter-prediction information to the merge candidate list.

The processing unit may generate combined inter-prediction informationby combining two or more of pieces of inter-prediction information forneighbor blocks of the target block with each other.

The processing unit may configure an inter-prediction informationpalette. The inter-prediction information palette may be a list having Npieces of inter-prediction information. N may be a positive integer.Here, the processing unit may 1) add the inter-prediction mode of atarget block to the inter-prediction information palette and 2) managethe inter-prediction mode in the inter-prediction information palettedepending on the specific sequence and method. For example, when theinter-prediction information palette is filled up with information, theprocessing unit may manage the inter-prediction information palette in aFirst-in First-Out (FIFO) manner.

When the inter-prediction information of the target block is identicalto inter-prediction information present in the inter-predictioninformation palette (that is, when the inter-prediction information ofthe target block is already included in the inter-prediction informationpalette), the processing unit may not add the inter-predictioninformation of the target block to the inter-prediction informationpalette.

When the inter-prediction information of the target block is identicalto inter-prediction information present in the inter-predictioninformation palette, the processing unit may move the inter-predictioninformation of the inter-prediction information palette, which isidentical to the inter-prediction information of the target block, tothe location of first inter-prediction information in theinter-prediction information palette. In other words, the processingunit may assign a specific priority, such as the highest priority, tothe inter-prediction information of the inter-prediction informationpalette, which is identical to the inter-prediction information of thetarget block, and may adjust the locations of pieces of inter-predictioninformation present in the inter-prediction information palette based onthe assigned priorities.

The processing unit may initialize the inter-prediction informationpalettes for all blocks in a target picture to the unit of each picture.In other words, the blocks in the target picture may share a singleinter-prediction information palette with each other.

The processing unit may use inter-prediction information present in theinter-prediction information palette as inter-prediction information ofa temporal neighbor block.

FIG. 15 illustrates spatial neighbor blocks of a target block accordingto an example.

In FIG. 15, A to K may indicate respective spatial neighbor blocks.

The inter-prediction information of a spatial neighbor block may beinter-prediction information of a block present at any one of locationscorresponding to A to K of FIG. 15.

Hereinafter, the term “inter-prediction information of block X” may beunderstood to be “inter-prediction information corresponding to thelocation of X”.

For example, the size of the neighbor block may be M×N. M and N may eachbe at least one of 2, 4, 8, 16, 32, 64, and 128.

Left neighbor blocks may be neighbor blocks adjacent to the left of thetarget block, and may be one or more of block A, block B, block C, blockD, and block E.

Above neighbor blocks may be neighbor blocks adjacent to the top of thetarget block, and may be one or more of block G, block H, block I, blockJ, and block K.

An above-left neighbor block may be a neighbor block that is adjacent toan above-left corner of the target block, and may be block F.

Such a spatial neighbor block may be a block that is adjacent to theboundary of the target block or that is not adjacent thereto.

FIG. 16 illustrates temporal neighbor blocks of a target block accordingto an example.

In FIG. 16, L to W may denote respective temporal neighbor blocks.

The temporal neighbor blocks may be blocks in a previous picture. Theprevious picture may be a previously reconstructed col picture. Theprevious picture may be a picture on which encoding or decoding has beenperformed before the target picture is encoded or decoded.

The previous picture may be a picture having a Picture Order Count (POC)larger than that of the target picture.

The location of a temporal neighbor block in the previous picture may heidentical to that of a target block in the target picture.Alternatively, the location of the temporal neighbor block in theprevious picture may correspond to that of the target block in thetarget picture. Alternatively, the location of the temporal neighborblock in the previous picture may correspond to at least one of thelocation of a below-right portion of the target block, a central portionof the target block, and a specific location of the target block.

Alternatively, the temporal neighbor block may be a block adjacent to acol block. For example, the temporal neighbor block may be a blockadjacent to a below-right vertex of the col block.

Alternatively, the temporal neighbor block may be a temporally previousblock in the target picture. The temporally previous block may be ablock on which encoding or decoding has been performed before the targetblock is encoded or decoded.

The temporal neighbor block may be a specific neighbor block that isreferred to in a procedure for configuring a merge candidate list. Here,the specific neighbor block may be a neighbor block corresponding tointer-prediction information included in the merge candidate list.

The inter-prediction information of the temporal neighbor block may beinter-prediction information of a block disposed at a specific locationin the previous picture. Here, the specific location may be the locationof the target block in the target picture.

The inter-prediction information of the temporal neighbor block may beinter-prediction information of a block disposed at a specific locationin the target picture. Here, the specific location may be the locationof a spatial neighbor block of the target block in the target picture.

Configuration of Merge Candidate List Using Combined Inter-PredictionInformation

FIG. 17 illustrates the generation of combined inter-predictioninformation of an above-right neighbor block according to an example.

FIG. 18 illustrates the generation of combined inter-predictioninformation of an above neighbor block according to an example.

The processing unit may configure a merge candidate list using combinedinter-prediction information. The combined inter-prediction informationmay replace the inter-prediction information or motion information of aneighbor block, and may then be added, as a new merge candidate, to themerge candidate list.

The processing unit may generate combined inter-prediction informationby combining multiple pieces of inter-prediction information related tothe target block. For example, the inter-prediction information relatedto the target block may be inter-prediction information for a neighborblock of the target block. The inter-prediction information related tothe target block may be neighbor inter-prediction information. Theneighbor inter-prediction information may be the inter-predictioninformation of a neighbor block.

The combined inter-prediction information may contain motioninformation. The motion information of the combined inter-predictioninformation may contain at least one of a reference picture list, areference picture index, an inter-prediction indicator, a motion vector,a motion vector candidate, a motion vector candidate list, and a PictureOrder Count (POC).

In an embodiment, the term “inter-prediction information” may bereplaced with “motion information” and “motion vector”, and “combinedinter-prediction information” may be replaced with “combined motioninformation” and “combined motion vector”.

The processing unit may select neighbor inter-prediction information tobe used from among multiple pieces of neighbor inter-predictioninformation when generating partial information of the combinedinter-prediction information.

For example, the processing unit may use partial information of theselected neighbor inter-prediction information as the partialinformation of the combined inter-prediction information. In otherwords, the processing unit may assign the value of the partialinformation of the selected neighbor inter-prediction information to thepartial information of the combined inter-prediction information.

For example, the partial information may be either an IC flag or an OBMCflag.

For example, the processing unit may generate partial information of thecombined inter-prediction information using neighbor inter-predictioninformation selected in relation to the combination of motion vectorsfrom among multiple pieces of neighbor inter-prediction information.

For example, the processing unit may generate partial information of thecombined inter-prediction information using neighbor inter-predictioninformation that is a reference of scaling for a combination of motionvectors from among multiple pieces of neighbor inter-predictioninformation.

For example, referring to FIG. 15, when combined inter-predictioninformation for block F is generated using pieces of inter-predictioninformation of block B and block J, an IC flag and/or an OBMC flag ofblock B or block J may be used as the IC flag and/or OBMC flag of blockF.

The processing unit may generate the motion vector of combinedinter-prediction information by combining the motion vectors of thepieces of neighbor motion information. The neighbor motion informationmay be the motion information of a neighbor block. Also, a neighbormotion vector may be the motion vector of a neighbor block.

For example, the neighbor motion information may be the motioninformation of blocks, such as spatial neighbor blocks A to Killustrated in FIG. 15 and the temporal neighbor blocks L to Willustrated in FIG. 16.

The neighbor motion information may be the motion information of eachblock that is not adjacent to the target block. The block that is notadjacent to the target block may be a block adjacent to the neighborblock of the target block.

The neighbor motion information may be the motion information of theblock having the above-described specific relationship with the targetblock, and the block having the specific relationship may also be ablock that is not adjacent to the target block. For example, the blockhaving the specific relationship may be a block that is adjacent to theneighbor block of the target block. The neighbor block may be interposedbetween the block having the specific relationship and the target block.

The combined inter-prediction information may be the result obtained byselecting one from among pieces of motion information of the multipleneighbor blocks. Here, one of the pieces of motion information may beselected as the combined inter-prediction information according to aspecified condition. For example, the combined inter-predictioninformation may be the result of calculation, selection, combination,and transformation that use the pieces of motion information of multipleneighbor blocks.

For example, the combined inter-prediction information may be the motioninformation of a neighbor block for which the difference between the POCof the target picture and the POC of a reference picture for theneighbor block is the smallest.

For example, the combined inter-prediction information may be specificmotion information present in a merge candidate list.

The combined inter-prediction information may be the result obtained byselecting and combining one or more from among multiple pieces ofneighbor motion information. Here, the combined inter-predictioninformation may be selected according to the specified condition.

For example, the motion vector of the combined inter-predictioninformation may be the motion vector of a specific neighbor block amongmultiple neighbor blocks. Here, the specific neighbor block may be aneighbor block for which the difference between the POC of the targetpicture and the POC of the reference picture for the neighbor block isthe smallest, among the multiple neighbor blocks. The motion vector ofthe combined inter-prediction information may be the result of a formulathat uses multiple neighbor motion vectors. The neighbor motion vectormay be the motion vector of a neighbor block. The neighbor motion vectorof the neighbor block may include multiple motion vectors.

When the combined inter-prediction information is generated, theprocessing unit may generate unidirectional combined inter-predictioninformation or bidirectional combined inter-prediction information.Here, the unidirectional combined inter-prediction information may beforward (L0) inter-prediction information or backward (L1)inter-prediction information, and the bidirectional combinedinter-prediction information may be forward and backwardinter-prediction information.

The unidirectional combined inter-prediction information may be thecombination of 1) pieces of bidirectional inter-prediction informationof the neighbor block, 2) pieces of unidirectional predictioninformation of the neighbor block, and 3) pieces of L0 or L1inter-prediction information in pieces of combined inter-predictioninformation.

For example, the processing unit may generate L0 (L1) directionalinter-prediction information by combining two or more temporal neighborblocks, and may add the generated unidirectional prediction informationto the merge candidate list.

For example, the combined inter-prediction information may be the resultof the combination of pieces of L0 (L1) directional inter-predictioninformation of two previous blocks and L0(L1) directionalinter-prediction information of one temporal neighbor block, and maythen be added to the merge candidate list.

For example, the combined inter-prediction information may be the resultof the combination of pieces of L0(L1) directional inter-predictioninformation of two specific neighbor blocks referred to in a mergecandidate list configuration procedure, and may be added to the mergecandidate list.

The bidirectional combined inter-prediction information may be acombination of the above-described forward inter-prediction informationand backward inter-prediction information.

The motion vector of the combined inter-prediction information may bethe combination of neighbor motion vectors. For example, the neighbormotion information may be the combination of pieces of motioninformation of multiple neighbor blocks A to W. For example, the motionvector of the combined inter-prediction information may be the averagevalue, maximum value, minimum value or median value of the multipleneighbor motion vectors, and may be the combination of one or more ofthe average value, maximum value, minimum value, and median value.

The average value may be obtained by dividing the sum of combined motionvectors by the number of combined motion vectors. For example, theaverage value of motion vector (4, 6) and motion vector (6, 10) may be(5, 8).

For example, the motion vector of the combined inter-predictioninformation may be a weighted average of multiple neighbor motionvectors, or may be a combination that uses variation between themultiple neighbor motion vectors,

For example, as illustrated in FIG. 17, for a target block 1710, theremay be an above-left neighbor block 1720, an above neighbor block 1730,an above-right neighbor block 1740, a left neighbor block 1750, and abelow-left neighbor block 1760. By the combination of the motioninformation 1721 of the above-left neighbor block 1720 and the motioninformation 1731 of the above neighbor block 1730, combinedinter-prediction information corresponding to the motion information1741 of the above-right block 1740 may be generated. Such combinedinter-prediction information may be used as the motion information 1711of the target block 1710.

For example, as illustrated in FIG. 18, by the combination of the motioninformation 1721 of the above-left neighbor block 1720 and the motioninformation 1741 of the above-right neighbor block 1740, combinedinter-prediction information corresponding to the motion information1731 of the above neighbor block 1730 may be generated. Such combinedinter-prediction information may be used as the motion information 1711of the target block 1710.

As described above, the motion vector of the combined inter-predictioninformation may be the result of a weighted combination of neighbormotion vectors. A higher weight may be allocated to the motion vector ofa neighbor block having a higher correlation with the target block.

The motion vector of the combined inter-prediction information may bethe result of a weighted combination of neighbor motion vectors based ona block size (i.e. weighted combination based on block size). Theweighted combination based on block size may be represented by thefollowing Equation 2:

$\begin{matrix}\frac{{{MV}_{Left} \times {width}} + {{MV}_{Above} \times {height}}}{{width} + {height}} & \left\lbrack {{Equation}\mspace{14mu} 2} \right\rbrack\end{matrix}$

MV_(Left) may be the left neighbor motion vector of the target block.The left neighbor motion vector of the target block may be the motionvector of a neighbor block adjacent to the left of the target block.

“Width” may denote the width of the target block, and may be a weightfor the left neighbor motion vector of the target block.

MV_(Above) may be the above neighbor motion vector of the target block.The above neighbor motion vector of the target block may be the motionvector of a neighbor block adjacent to the top of the target block.

“Height” may denote the height of the target block, and may be a weightfor the above neighbor motion vector of the target block.

The motion vector of the combined inter-prediction information may bethe result of a weighted combination of neighbor motion vectors based onPOC (i.e. weighted combination based on POC).

For example, as the POC of a reference picture for neighbor motioninformation is closer to the POC of the target picture, the weight forthe neighbor motion vector may be greater.

The combination using variation may be the generation ofinter-prediction information of a block previous to the combined blocksor a block subsequent to the combined blocks using the variation betweentwo or more motion vectors.

For example, referring to FIG. 15, the processing unit may derive themotion vector of block K through a combination that uses variationbetween the motion vector of block I and the motion vector of block J.The motion vector of block K may be obtained by adding the differencebetween the motion vector of block J and the motion vector of block I tothe motion vector of block J.

Alternatively, the motion vector of the combined inter-predictioninformation may be the result of an extrapolation-based combination ofneighbor motion vectors.

For example, the extrapolation-based combination of two neighbor motionvectors may be represented by the following Equation 3:2×MV₀−MV₁  [Equation 3]

MV₀ may be a first neighbor motion vector. MV₁ may be a second neighbormotion vector.

Scaling may be applied to inter-prediction information that is used togenerate combined inter-prediction information.

For example, when neighbor motion information indicates bidirectionalprediction, the processing unit may scale the motion vector of L0 basedon the motion vector of L1. The processing unit may generate combinedinter-prediction information by combining the scaled motion vector of L0with the motion vector of L1.

For example, when neighbor motion information indicates bidirectionalprediction, the processing unit may scale the motion vector of L1 basedon the motion vector of L0. The processing unit may generate combinedinter-prediction information by combining the scaled motion vector of L1with the motion vector of L0, and may add the generated combinedinter-prediction information to the merge candidate list.

When reference pictures for multiple pieces of neighbor motioninformation that are used to generate combined inter-predictioninformation are different from each other, the processing unit maychange inter-prediction information by applying scaling to theinter-prediction information.

For example, referring to FIG. 15, when neighbor blocks used forcombination are block B and block J, and reference pictures for block Band block J are different from each other, the processing unit may scalethe motion vector of block J depending on the temporal distance betweenthe block B and the reference picture for the block B.

For example, referring to FIG. 15, when neighbor blocks used forcombination are block B and block J, and reference pictures for block Band block J are different from each other, the processing unit may scalethe motion vector of block B depending on the temporal distance betweenthe block J and the reference picture of the block J.

In scaling, the processing unit may select neighbor motion informationthat is a reference for scaling.

The processing unit may select neighbor motion information that is areference for scaling based on POC. The processing unit may select, asreference motion information, motion information for which the POC of areference picture for motion information is closer to the POC of thetarget picture from among multiple pieces of neighbor motioninformation.

When the combined inter-prediction information is generated, theprocessing unit may determine whether to perform combination based on aspecified condition.

When the combined inter-prediction information is generated, theprocessing unit may determine whether to perform combination based onsimilarity between pieces of inter-prediction information or pieces ofmotion information that are used for combination. For example, whensimilarity is less than a predefined threshold value, the processingunit may not perform combination. Alternatively, when similarity isgreater than a predefined threshold value, the processing unit may notperform combination.

Here, the similarity may indicate the value or result of a formula thatuses pieces of motion information.

The processing unit may generate combined inter-prediction informationby combining pieces of neighbor motion information based on thedirections of reference pictures for the neighbor motion information.For example, the processing unit may generate combined inter-predictioninformation by combining neighbor motion vectors in the same direction.

As described above, the processing unit may generate combinedinter-prediction information by combining pieces of inter-predictioninformation of multiple blocks. Here, each of the multiple blocks may bea block that satisfies the specified condition.

In each block illustrated in FIG. 15, inter-prediction information of aspecific block may be replaced with combined inter-predictioninformation. The processing unit may derive first inter-predictioninformation for the location to the left of a specific block and derivesecond inter-prediction information for the location to the right of thespecific block, and may generate combined inter-prediction informationby combining the first inter-prediction information with the secondinter-prediction information. The generated combined inter-predictioninformation may replace the inter-prediction information of the specificblock. Here, the inter-prediction information for the location to theleft of the specific block may be inter-prediction information of ablock located to the left of the specific block. Here, theinter-prediction information for the location to the right of thespecific block may be inter-prediction information of a block located tothe right of the specific block. Further, such derivation, combination,and generation may also be applied to a portion of inter-predictioninformation, such as motion information and motion vectors.

For example, when the first inter-prediction information for the leftlocation is derived, if the inter-prediction information of only oneblock located to the left of the specific block is available, theprocessing unit may use the available inter-prediction information forcombination.

For example, when the second inter-prediction information for the rightlocation is derived, if the inter-prediction information of only oneblock located to the right of the specific block is available, theprocessing unit may use the available inter-prediction information forcombination.

For example, when multiple pieces of inter-prediction information ofmultiple blocks located to the left of the specific block are available,the processing unit may derive first inter-prediction information bycombining the available multiple pieces of inter-prediction information.

For example, when multiple pieces of inter-prediction informationlocated to the right of the specific block are available, the processingunit may derive second inter-prediction information by combining theavailable multiple pieces of inter-prediction information.

For example, when the first inter-prediction information for the leftlocation is derived, if multiple pieces of inter-prediction informationof multiple blocks located to the left of the specific block areavailable, the processing unit may select, as the first inter-predictioninformation, specific inter-prediction information from among themultiple pieces of inter-prediction information, and may use theselected inter-prediction information for the generation of combinedinter-prediction information.

For example, if multiple pieces of inter-prediction information ofmultiple blocks located to the left of the specific block are available,the processing unit may select the block having the shortest temporaldistance from the target picture from among the multiple blocks. Theprocessing unit may select the inter-prediction information of theselected block as the first inter-prediction information. The temporaldistance between pictures may be the difference between the sequentialpositions at which the pictures are displayed.

For example, when the second inter-prediction information for the rightlocation is derived, if multiple pieces of inter-prediction informationof multiple blocks located to the right of the specific block areavailable, the processing unit may select, as the secondinter-prediction information, specific inter-prediction information fromamong the multiple pieces of inter-prediction information, and may usethe selected inter-prediction information for the generation of combinedinter-prediction information.

For example, if multiple pieces of inter-prediction information ofmultiple blocks located to the right of the specific block areavailable, the processing unit may select the block having the shortesttemporal distance from the target picture from among the multipleblocks. The processing unit may select the inter-prediction informationof the selected block as the second inter-prediction information.

For example, in the individual blocks illustrated in FIG. 15, whenmultiple pieces of inter-prediction information of multiple blockslocated to the left of the specific block are available, the processingunit may generate combined inter-prediction information by combining themultiple pieces of inter-prediction information. The generated combinedinter-prediction information may replace the inter-predictioninformation of the specific block. Further, when multiple pieces ofinter-prediction information of multiple blocks located to the right ofthe specific block are available, the processing unit may generatecombined inter-prediction information by combining the multiple piecesof inter-prediction information.

For example, in a specific block among block N, block O, block P, andblock Q of FIG. 16, when pieces of inter-prediction information ofmultiple co-located blocks in different multiple previous pictures areavailable, the processing unit may generate combined inter-predictioninformation by combining the pieces of available inter-predictioninformation. The generated combined inter-prediction information mayreplace the inter-prediction information of the specific block. Such aco-located block may be a col block for the specific block. In otherwords, the locations of the co-located blocks in different previouspictures may be identical to those of the specific block in the previouspictures.

For example, combined inter-prediction information for block N may bethe combination of pieces of inter-prediction information for theco-located blocks L and M. For example, combined inter-predictioninformation for block O may be the combination of pieces ofinter-prediction information for the co-located blocks U and R. Forexample, combined inter-prediction information for block P may be thecombination of pieces of inter-prediction information for the co-locatedblocks V and S. For example, combined inter-prediction information forblock Q may be the combination of pieces of inter-prediction informationfor the co-located blocks W and T.

For example, the processing unit may generate combined inter-predictioninformation by combining one or more pieces of inter-predictioninformation of one or more spatial neighbor blocks with one or morepieces of inter-prediction information of one or more temporal neighborblocks.

FIG. 19 illustrates the generation of combined inter-predictioninformation of neighbor blocks according to an example.

In FIG. 19, a target CU may indicate a target block.

In FIG. 19, block AL, block A, block AR, block L, and block LB may bethe above-left neighbor block, above neighbor block, above-rightneighbor block, left neighbor block, and below-left neighbor block of atarget block, respectively.

The above neighbor block may refer to a rightmost (or leftmost) block,among multiple neighbor blocks above the target block. The left neighborblock may refer to a lowermost (or uppermost) block, among multipleneighbor blocks to the left of the target block.

The block A and the block AR may be understood to be multiple blocksthat are adjacent to the top of the target block or are located abovethe target block. The block L and the block LB may be understood to bemultiple blocks that are adjacent to the left of the target block or arelocated to the left of the target block.

The processing unit may generate first neighbor inter-predictioninformation by combining the pieces of inter-prediction information ofthe block A and the block AR, wherein the pieces of inter-predictioninformation may be understood to be above inter-prediction informationor above motion vectors. The processing unit may generate secondneighbor inter-prediction information by combining pieces ofinter-prediction information of the block L and the block LB. Thesepieces of inter-prediction information may be understood to be leftinter-prediction information or left motion vectors. The processing unitmay generate combined inter-prediction information by combining thefirst neighbor inter-prediction information with the second neighborinter-prediction information.

When the inter-prediction information of the block AL is not available,the processing unit may replace the inter-prediction information of theblock AL with the generated combined inter-prediction information.Alternatively, the processing unit may add the combined inter-predictioninformation generated for the block AL as a new merge candidate to amerge candidate list.

When the above-described first neighbor inter-prediction information,second neighbor inter-prediction information, and combinedinter-prediction information are acquired, the foregoing combinationmethods and combination methods that will be described below may beused.

When only one of pieces of inter-prediction information of the block Aand the block AR is available, the processing unit may use availableinter-prediction information, among the pieces of inter-predictioninformation, as the first neighbor inter-prediction information.Further, when only one of pieces of inter-prediction information of theblock L and the block LB is available, the processing unit may use theavailable inter-prediction information, among the pieces ofinter-prediction information, as the second neighbor inter-predictioninformation.

The processing unit may select any one of the pieces of inter-predictioninformation of the block A and the block AR, and may use the selectedinter-prediction information as the first neighbor inter-predictioninformation. The processing unit may select any one of the pieces ofinter-prediction information of the block L and the block LB, and mayuse the selected inter-prediction information as the second neighborinter-prediction information.

The processing unit may select inter-prediction information having a POCcloser to the POC of the target picture, among pieces ofinter-prediction information of the block A and the block AR, as thefirst neighbor inter-prediction information. Here, the POC of theinter-prediction information may be a POC for the motion information ofthe inter-prediction information.

The processing unit may select inter-prediction information having a POCcloser to the POC of the target picture, among pieces ofinter-prediction information of the block L and the block LB, as thesecond neighbor inter-prediction information.

FIG. 20 illustrates the generation of inter-prediction information ofblock AL according to an example.

MV0 and MV1 may refer to respective motion vectors used for combinedinter-prediction information.

The processing unit may generate combined inter-prediction informationby combining pieces of inter-prediction information of block L and blockLB. The combined inter-prediction information may replace theinter-prediction information of the block AL, and may be added as amerge candidate to a merge candidate list for a target block.

FIG. 21 illustrates the generation of inter-prediction information ofblock AR according to an example.

The processing unit may generate combined inter-prediction informationby combining pieces of inter-prediction information of block A and blockL. The combined inter-prediction information may replace theinter-prediction information of the block AR, and may be added as amerge candidate to a merge candidate list for a target block. Forexample, the foregoing combination may be extrapolation-basedcombination.

FIG. 22 illustrates the generation of inter-prediction information of atarget CU according to an example.

The processing unit may generate combined inter-prediction informationby combining pieces of inter-prediction information of block L and anon-adjacent block. The combined inter-prediction information may beadded as a merge candidate to a merge candidate list for a target block.For example, the foregoing combination may be extrapolation-basedcombination.

Generation of Combined Inter-Prediction Information UsingInter-Prediction Information in Merge Candidate List

The processing unit may generate combined inter-prediction informationby combining M pieces of inter-prediction information in a mergecandidate list, and may use the generated combined inter-predictioninformation for inter prediction, or may add the generated combinedinter-prediction information to the merge candidate list.

Here, the directions of motion vectors of multiple pieces ofinter-prediction information that are combined may be identical to eachother.

Here, M may be an integer of 2 or more, and may be less than or equal tothe number of pieces of inter-prediction information in the mergecandidate list.

For example, combinations that can be used when three pieces ofinter-prediction information are present in the merge candidate list andthe value of M is 2 may be (first inter-prediction information, secondinter-prediction information), (first inter-prediction information,third inter-prediction information), and (second inter-predictioninformation, third inter-prediction information), and the processingunit may generate combined inter-prediction information by combining thepieces of inter-prediction information depending on these combinations.

For example, a combination that can be used when four pieces ofinter-prediction information are present in the merge candidate list andthe value of M is 4 may be (first inter-prediction information, secondinter-prediction information, third inter-prediction information, andfourth inter-prediction information), and the processing unit maygenerate combined inter-prediction information by combining the piecesof inter-prediction information depending on the combination.

Configuration of Merge Candidate List

As described above, the processing unit may add pieces ofinter-prediction information of neighbor blocks as merge candidates to amerge candidate list when the merge candidate list is configured. Here,the processing unit may add the pieces of inter-prediction informationof neighbor blocks to the merge candidate list in the specific sequenceof the neighbor blocks.

Referring back to FIG. 15, the processing unit may use pieces ofinter-prediction information of specific spatial neighbor blocks asmerge candidates when configuring a merge candidate list. The specificspatial neighbor blocks may be block A, block B, block F, block J, andblock K.

The processing unit may add 1) combined inter-prediction information, 2)a sub-block-based motion information derivation mode (e.g. AlternativeTemporal Motion Vector Prediction (ATMVP) mode, a Spatial-TemporalMotion Vector Prediction (STMVP) mode, etc.), and 3) an affine spacemotion information derivation mode to the merge candidate list in aspecific sequence.

For example, the processing unit may configure the merge candidate listin the sequence of (B, J, K, A, ATMVP, F, combined inter-predictioninformation).

For example, the processing unit may configure the merge candidate listin the sequence of (B, J, K, A, first combined inter-predictioninformation, ATMVP, F, second combined inter-prediction information).Here, the first combined inter-prediction information and the secondcombined inter-prediction information may be different from each otherin neighbor blocks to be referred to for the generation thereof, thenumber of neighbor blocks, and the directionality of combinedinter-prediction information.

Below, “(α, β, γ, δ, ε)” may indicate the sequence of blocks, and mayrepresent that the block of a symbol appearing earlier in theparentheses is processed earlier than the block of a symbol appearinglater. The expression that a merge candidate list is configured in thesequence of “(α, β, γ, δ, ε)” may mean that, in the configuration of themerge candidate list, the task for configuring the merge candidate listis performed in the sequence of block α, block β, block γ, block δ, andblock ε, and may also mean that the blocks are processed in the sequenceof the listed blocks.

Here, the processing unit may perform the following tasks 1) to 5) oneach of the blocks in the sequence of the blocks.

1) The processing unit may determine whether to add the inter-predictioninformation of the corresponding block to the merge candidate list.

2) If it is determined to add the inter-prediction information of theblock to the merge candidate list, the processing unit may add theinter-prediction information of the block to the merge candidate list.

3) (If it is determined not to add the inter-prediction information ofthe block to the merge candidate list), the processing unit maydetermine whether to derive combined inter-prediction information forthe corresponding block.

4) If it determined to derive combined inter-prediction information, theprocessing unit may derive the combined inter-prediction information.

5) The processing unit may determine whether to add the combinedinter-prediction information to the merge candidate list.

6) If it is determined to add the combined inter-prediction informationto the merge candidate list, the processing unit may add the combinedinter-prediction information to the meme candidate list.

When tasks 1) to 5) are performed on one block, task 1) may be performedon a subsequent block.

For example, the processing unit may configure a merge candidate list inthe sequence of (B, J, K, A, F).

For example, the processing unit may configure a merge candidate list inthe sequence of (J, B, A, K, F).

FIG. 23 illustrates the case where a CU of which the width and heightare the same is vertically split.

FIG. 24 illustrates the case where a CU of which the width and heightare the same is horizontally split.

FIG. 25 illustrates the case where a CU having a width greater than aheight is vertically split.

FIG. 26 illustrates the case where a CU having a height greater than awidth is horizontally split.

The comparison between the width and the height and the direction ofsplitting may be used to determine the sequence of neighbor blocks.

The processing unit may determine a scheme for configuring the mergecandidate list based on the shape of a target block.

The scheme for configuring the merge candidate list may include thesequence of neighbor blocks needed to configure the merge list. Thesequence of neighbor blocks may be the sequence of an availability testfor pieces of inter-prediction information of neighbor blocks and theaddition of the pieces of inter-prediction information.

When the height of the target block is greater than the width of thetarget block, the processing unit may configure a merge candidate listin the sequence of (J, B, K, A, F), whereas when the height of thetarget block is less than or equal to the width of the target block, theprocessing unit may configure the merge candidate list in the sequenceof (B, J, K, A, F).

When the height of the target block is greater than the width of thetarget block, the processing unit may configure a merge candidate listin the sequence of (J, B, A, K, F), whereas when the height of thetarget block is less than or equal to the width of the target block, theprocessing unit may configure the merge candidate list in the sequenceof (B, J, K, A, F).

For example, when the height of the target block is greater than thewidth of target block, the processing unit may configure the mergecandidate list in the sequence of (J, K, B, A, F), when the height ofthe target block is less than the width of the target block, theprocessing unit may configure the merge candidate list in the sequenceof (B, A, J, K, F), and when the height and width of the target blockare equal to each other, the processing unit may configure the mergecandidate list in the sequence of (B, J, K, A, F).

For example, when the height of the target block is greater than thewidth of the target block, the processing unit may configure a mergecandidate list using pieces of inter-prediction information of spatialneighbor blocks located above the target block. When the height of thetarget block is greater than the width of the target block, theprocessing unit may configure a merge candidate list in the sequence of(F, G, H, I, J, K).

For example, when the height of the target block is less than the widthof the target block, the processing unit may configure a merge candidatelist using pieces of inter-prediction information of spatial neighborblocks located to the left of the target block. When the height of thetarget block is less than the width of the target block, the processingunit may configure a merge candidate list in the sequence of (A, B, C,D, E, F).

The processing unit may determine a scheme for configuring a mergecandidate list based on the state of splitting of the target block.

The state of splitting may mean the direction of splitting. Thesplitting state of the target block may be the type or direction ofsplitting that is used to generate the target block. Alternatively, thesplitting state of the target block may be the type or direction ofsplitting that is applied to the upper block of the target block.

For example, when the target block is obtained as a result of verticalsplitting, the processing unit may configure a merge candidate list inthe sequence of (J, B, K, A, F), whereas when the target block is notobtained as a result of vertical splitting, the processing unit mayconfigure the merge candidate list in the sequence of (B, J, K, A, F).

For example, when the target block is obtained as a result of verticalsplitting, the processing unit may configure a merge candidate list inthe sequence of (J, B, A, K, F), whereas when the target block is notobtained as a result of vertical splitting, the processing unit mayconfigure the merge candidate list in the sequence of (B, J, K, A, F).

For example, depending on which one of vertical splitting, horizontalsplitting, and quad-splitting has been used to obtain the target block,the processing unit may select one of different sequences of neighborblocks, and may configure a merge candidate list in the selectedsequence.

For example, when the target block is obtained as a result of verticalsplitting, the processing unit may configure a merge candidate list inthe sequence of (J, K, B, A, F). When the target block is obtained as aresult of horizontal splitting, the processing unit may configure amerge candidate list in the sequence of (B, A, J, K, F). When the targetblock is obtained as a result of quad-splitting, the processing unit mayconfigure a merge candidate list in the sequence of (B, J, K, A, F).

For example, when the target block is obtained as a result of verticalsplitting, the processing unit may configure a merge candidate listusing pieces of inter-prediction information of spatial neighbor blockslocated above the target block. When the target block is obtained as aresult of vertical splitting, the processing unit may configure a mergecandidate list in the sequence of (F, G, H, I, J, K).

For example, when the target block is obtained as a result of horizontalsplitting, the processing unit may configure a merge candidate listusing pieces of inter-prediction information of spatial neighbor blockslocated to the left of the target block. When the target block isobtained as a result of horizontal splitting, the processing unit mayconfigure a merge candidate list in the sequence of (A, B, C, D, E, F).

The processing unit may determine a scheme for configuring a mergecandidate list based both on the shape of the target block and on thesplitting state of the target block.

For example, when the height of the target block is greater than thewidth of the target block or when the height and width of the targetblock are equal to each other, and when the target block is obtained asa result of vertical splitting, the processing unit may configure amerge candidate list in the sequence of (J, B, K, A, F). In other cases,the processing unit may configure the merge candidate list in thesequence of (B, J, K, A, F).

For example, when the height of the target block is greater than thewidth of the target block or the height and width of the target blockare equal to each other, and when the target block is obtained as aresult of vertical splitting, the processing unit may configure a mergecandidate list in the sequence of (J, B, A, K, F). In other cases, theprocessing unit may configure the merge candidate list in the sequenceof (B, J, K, A, F).

For example, when the height of the target block is greater than thewidth of the target block or when the height and width of the targetblock are equal to each other, and when the target block is obtained asa result of vertical splitting, the processing unit may configure amerge candidate list in the sequence of (J, K, B, A, F). When the heightof the target block is less than the width of the target block or Whenthe target block is obtained as a result of horizontal splitting, theprocessing unit may configure a merge candidate list in the sequence of(B, A, J, K, F). When the height and width of the target block are equalto each other and when the target block is obtained as a result ofquad-splitting, the processing unit may configure a merge candidate listin the sequence of (B, J, K, A, F).

For example, when the height of the target block is greater than thewidth of the target block, or the height and width of the target blockare equal to each other, and when the target block is obtained as aresult of vertical splitting, the processing unit may configure a mergecandidate list using pieces of inter-prediction information of spatialneighbor blocks located above the target block. When the height of thetarget block is greater than the width of the target block, or theheight and width of the target block are equal to each other, and whenthe target block is obtained as a result of vertical splitting, theprocessing unit may configure a merge candidate list in the sequence of(F, G, H, I, J, K).

For example, when the height of the target block is less than the widthof the target block or When the target block is obtained as a result ofhorizontal splitting, the processing unit may configure a mergecandidate list using pieces of inter-prediction information of spatialneighbor blocks located to the left of the target block. When the heightof the target block is less than the width of the target block or whenthe target block is obtained as a result of horizontal splitting, theprocessing unit may configure a merge candidate list in the sequence of(A, B, C, D, E, F).

The processing unit may determine a scheme for configuring a mergecandidate list based on the location of the target block.

The location of the target block may be the relative location thereof inan upper block. By splitting the upper block, multiple partition blocksmay be generated, and the target block may be one of the multiplepartition blocks. The location of the target block may be the locationof the target block in the upper block or the location of the targetblock among the multiple partition blocks. Splitting may be binarysplitting or quad-splitting.

For example, in FIG. 23, the processing unit may apply a uniformconfiguration method to a merge candidate list for a first partition CUand apply an adaptive configuration method to a merge candidate list fora second partition CU.

The processing unit may determine a scheme for configuring a mergecandidate list based on whether there is combined inter-predictioninformation. In the configuration of a merge candidate list, theprocessing unit may adjust the priority of combined inter-predictioninformation when there is combined inter-prediction information. Here,the priority may refer to the location of combined inter-predictioninformation in the merge candidate list, the index of the combinedinter-prediction information or the sequence of addition of the combinedinter-prediction information to the merge candidate list.

For example, when the merge candidate list is configured in the sequenceof (B, J, K, A, F), if block B has combined inter-predictioninformation, the processing unit may configure the merge candidate listin the sequence of (J, K, A, F, B). In other words, the processing unitmay assign the lowest priority to the combined inter-predictioninformation. Alternatively, in the configuration of a merge candidatelist, the processing unit may add the combined inter-predictioninformation to a location in the merge candidate list subsequent topieces of inter-prediction information. In other words, the processingunit may add the combined inter-prediction information to the mergecandidate list with lower priority to follow pieces of inter-predictioninformation of neighbor blocks.

For example, when the merge candidate list is configured in the sequenceof (B, J, K, N, F) and block N has a temporal neighbor block, if block Fhas combined inter-prediction information, the processing unit mayconfigure a merge candidate list in the sequence of (B, J, K, F, N). Inother words, the processing unit may assign priority that is lower thanthose of pieces of inter-prediction information of spatial neighborblocks and is higher than that of inter-prediction information of thetemporal neighbor block to the combined inter-prediction information.

Alternatively, in the configuration of a merge candidate list, theprocessing unit may add combined inter-prediction information to alocation in the merge candidate list that is subsequent tointer-prediction information of a spatial neighbor block and is previousto inter-prediction information of a temporal neighbor block.Alternatively, the processing unit may assign combined inter-predictioninformation a priority that is higher than that of inter-predictioninformation of a temporal neighbor block. Alternatively, in theconfiguration of a merge candidate list, the processing unit may addcombined inter-prediction information to a location in the mergecandidate list that is previous to inter-prediction information of atemporal neighbor block.

For example, when there are multiple pieces of combined inter-predictioninformation, the sequence of the multiple pieces of combinedinter-prediction information may be maintained without change dependingon the above-described sequence determination scheme.

The processing unit may determine a method for configuring a mergecandidate list based on the depth of a target block. The depth of thetarget block may be at least one of a Quad-Tree (QT) depth based on QTsplitting and a Binary tree (BT) depth based on BT splitting.

For example, the processing unit may determine a scheme for configuringa merge candidate list based on whether the depth of a target blockfalls within a specific range.

For example, when the BT depth of the target block is less than or equalto n, the processing unit may configure a merge candidate list using atleast one of the above-described scheme for configuring the mergecandidate list based on the shape of the target block and theabove-described scheme for configuring the merge candidate list based onthe splitting state of the target block. For example, n may be 1.

In an embodiment, when the QT depth of the target block is equal to orgreater than n and the BT depth thereof is less than or equal to m, theprocessing unit may configure a merge candidate list using at least oneof the above-described scheme for configuring the merge candidate listbased on the shape of the target block and the above-described schemefor configuring the merge candidate list based on the splitting state ofthe target block. For example, n may be 3, and m may be 1.

The processing unit may determine a scheme for configuring a mergecandidate list based on the location of the target block and the depthof the target block.

For example, when the BT depth of the target block is less than or equalto n and the target block is a block located in a lower portion, amongpartition blocks generated by horizontal splitting, the processing unitmay configure a merge candidate list using at least one of theabove-described scheme for configuring the merge candidate list based onthe shape of the target block and the above-described scheme forconfiguring the merge candidate list based on the splitting state of thetarget block. Here, n may be 1.

Configuration of AMVP Candidate List

The processing unit may derive inter-prediction information of a targetblock using an AMVP mode.

The processing unit may configure an AMVP candidate list. The number ofAMVP candidates in the AMVP candidate list may be N. N may be a positiveinteger. For example, the AMVP candidate list may include two AMVPcandidates.

For example, such an AMVP candidate may be inter-prediction informationor motion information. Alternatively, the AMVP candidate may include amotion vector or a reference picture list.

The processing unit may configure an AMVP candidate list using one ormore of inter-prediction information of a spatial neighbor block, interprediction information of a temporal neighbor block, and combinedinter-prediction information.

The processing unit may derive one AMVP candidate from inter-predictioninformation of a neighbor block to the left of a target block, and mayderive one AMVP candidate from inter-prediction information of aneighbor block above the target block. When the AMVP candidate list isnot filled up with candidates, the processing unit may derive anadditional AMVP candidate from inter-prediction information of thetemporal neighbor block.

The processing unit may derive an AMVP candidate using pieces ofinter-prediction information of neighbor blocks in the specific sequenceof the neighbor blocks, and may add the derived AMVP candidate to theAMVP candidate list. Here, the AMVP candidate list may be differentlyconfigured in the sequence of neighbor blocks, and the predictionefficiency and coding efficiency of encoding and decoding that use theAMVP candidate list may vary depending on the sequence of neighborblocks.

The processing unit may derive a scheme AMVP candidate in the specificsequence of left neighbor blocks. Here, the derivation of the AMVPcandidate in the specific sequence of neighbor blocks may mean that theAMVP candidate is derived using pieces of inter-prediction informationof neighbor blocks selected in the specific sequence.

In the derivation of an AMVP candidate in the specific sequence ofneighbor blocks, when inter-prediction information of a neighbor blockat the current sequential position is available, the processing unit mayderive an AMVP candidate using the inter-prediction information of theneighbor block at the current sequential position. When inter-predictioninformation of the neighbor block at the current sequential position isunavailable, the processing unit may derive an AMVP candidate usinginter-prediction information of a neighbor block at a subsequentsequential position, in other words, the processing unit may derive anAMVP candidate using inter-prediction information of a precedingneighbor block that appears first and has available inter-predictioninformation, among neighbor blocks.

The fact that inter-prediction information of a neighbor block isunavailable may mean that at least one of the following cases 1) to 3)is satisfied.

1) The case where inter-prediction information of a neighbor block isnot present

2) The case where a neighbor block and a target block are included indifferent slices, tiles, or pictures

3) The case where an AMVP candidate derived using inter-predictioninformation is identical to another AMVP candidate already included inan AMVP list, that is, the case where an AMVP candidate derived usingthe inter-prediction information is a duplicate AMVP candidate

For example, the processing unit may derive an AMVP candidate in thesequence of (A, B) upon deriving an AMVP candidate using left neighborblocks. In other words. When the inter-prediction information of block Ais available, an AMVP candidate derived by the inter-predictioninformation of block A may be may be included in the AMVP list, and whenthe inter-prediction information of block A is unavailable and theinter-prediction information of block B is available, an AMVP candidatederived by the inter prediction information of block B may be includedin the AMVP list.

For example, the processing unit may derive an AMVP candidate in thesequence of (B, A) upon deriving an AMVP candidate using left neighborblocks.

For example, the processing unit may derive an AMVP candidate in thesequence of (A, B, C, D, E) upon deriving an AMVP candidate using leftneighbor blocks.

The processing unit may derive an AMVP candidate in the specificsequence of above neighbor blocks.

For example, the processing unit may derive an AMVP candidate in thesequence of (K, J, F) upon deriving an AMVP candidate using aboveneighbor blocks.

For example, the processing unit may derive an AMVP candidate in thesequence of (K, F, J) upon deriving an AMVP candidate using aboveneighbor blocks.

When inter-prediction information of a neighbor block is not present oris unavailable, the processing unit may use, instead of theinter-prediction information of the neighbor block, combinedinter-prediction information in order to derive an AMVP candidate.

When configuring an AMVP candidate list using the inter-predictioninformation of a spatial neighbor block, the processing unit maydetermine a scheme for configuring an AMVP candidate list based on theshape of a target block.

For example, when the height of the target block is greater than thewidth of the target block, the processing unit may configure an AMVPlist using at least one of the following schemes 1) to 3).

1) The processing unit may derive one AMVP candidate frominter-prediction information of an above neighbor block of a targetblock, and may then derive one AMVP candidate from inter-predictioninformation of a left neighbor block of the target block.

2) The processing unit may configure an AMVP candidate list using onlypieces of inter-prediction information of above neighbor blocks of thetarget block.

3) The processing unit may configure an AMVP candidate list in thesequence of (J, B, K, A, F) or the sequence of (J, B, A, K, F).

For example, when the height of the target block is less than the widthof the target block, the processing unit may configure an AMVP listusing at least one of the following schemes 4) to 6).

4) The processing unit may derive one AMVP candidate frominter-prediction information of a left neighbor block of the targetblock, and may then derive one AMVP candidate from inter-predictioninformation of an above neighbor block of the target block.

5) The processing unit may configure an AMVP candidate list using onlypieces of inter-prediction information of left neighbor blocks of thetarget block.

6) The processing unit may configure an AMVP candidate list in thesequence of (B, J, K, A, F) or the sequence of (B, A, J, K, F).

For example, when the height of the target block is equal to the widthof the target block, the processing unit may configure an AMVP candidatelist using at least one of the following schemes 7) and 8).

7) The processing unit may configure an AMVP candidate list using atleast one of the above-described schemes 1) to 6).

8) The processing unit may configure an AMVP candidate list using piecesof inter-prediction information of left neighbor blocks of the targetblock and pieces of inter-prediction information of above neighborblocks of the target block.

The processing unit may determine a scheme for configuring an ANIVPcandidate list based on the splitting state of the target block.

For example, when the target block is obtained as a result of verticalsplitting, the processing unit may derive one AMVP candidate frominter-prediction information of an above neighbor block of the targetblock, and may then derive one AMVP candidate from inter-predictioninformation of a left neighbor block of the target block.

For example, when the target block is obtained as a result of horizontalsplitting, the processing unit may derive one AMVP candidate frominter-prediction information of a left neighbor block of the targetblock, and may then derive one AMVP candidate from inter-predictioninformation of an above neighbor block of the target block.

For example, the processing unit may configure an AMVP candidate listusing the above-described scheme for determining a merge candidate listbased on the splitting state of the target block.

The processing unit may determine a scheme for configuring an AMVPcandidate list based both on the shape of the target block and on thesplitting state of the target block.

For example, when the height of the target block is greater than thewidth of the target block or the height and width of the target blockare equal to each other, and when the target block is obtained as aresult of vertical splitting, the processing unit may derive one AMVPcandidate from the inter-prediction information of the above neighborblock for the target block, and may then derive one AMVP candidate fromthe inter-prediction information of the left neighbor block or the aboveneighbor block for the target block.

For example, when the height of a target block is less than the width ofthe target block or the height and width of the target block are equalto each other and when the target block is obtained as a result ofhorizontal splitting, the processing unit may derive one AMVP candidatefrom inter-prediction information of the left neighbor block for thetarget block, and may then derive one AMVP candidate from theinter-prediction information of the left neighbor block or the aboveneighbor block for the target block.

The processing unit may determine a scheme for configuring an AMVPcandidate list based on the location of the target block.

The location of the target block may be the relative location thereof inan upper block. By splitting the upper block, multiple partition blocksmay be generated, and the target block may be one of the multiplepartition blocks. The location of the target block may be the locationof the target block in the upper block or the location of the targetblock among the multiple partition blocks. Splitting may be binarysplitting or quad-splitting.

For example, in FIG. 23, the processing unit may apply a uniformconfiguration method to an AMVP candidate list for a first partition CUand apply an adaptive configuration method to an AMVP candidate list fora second partition CU.

The processing unit may determine a method for configuring an AMVPcandidate list based on the depth of a target block. The depth of thetarget block may be at least one of a Quad-Tree (QT) depth based on QTsplitting and a Binary tree (BT) depth based on BT splitting.

For example, the processing unit may determine a scheme for configuringair AMVP candidate list based on whether the depth of a target blockfalls within a specific range.

For example, when the BT depth of the target block is less than or equalto n, the processing unit may configure an AMVP candidate list using atleast one of the above-described scheme for configuring the AMVPcandidate list based on the shape of the target block and theabove-described scheme for configuring the AMVP candidate list based onthe splitting state of the target block. For example, n may be 1.

For example, when the QT depth of the target block is equal to orgreater than n and the BT depth thereof is less than or equal to m, theprocessing unit may configure the AMVP candidate list using at least oneof the above-described scheme for configuring an AMVP candidate listbased on the shape of the target block and the above-described schemefor configuring an AMVP candidate list based on the splitting state ofthe target block. For example, n may be 3, and m may be 1.

The processing unit may determine a scheme for configuring an AMVPcandidate list based on the location of the target block and the depthof the target block.

For example, when the BT depth of the target block is less than or equalto n and the target block is a block located in a lower portion, amongpartition blocks generated by horizontal splitting, the processing unitmay configure an AMVP candidate list using at least one of theabove-described scheme for configuring the AMVP candidate list based onthe shape of the target block and the above-described scheme forconfiguring the AMVP candidate list based on the splitting state of thetarget block. Here, n may be 1.

The details described in the above-described configurations of the mergecandidate list and the AMVP candidate list may be applied to each other.For example, features described in relation to the derivation andaddition of one of a merge candidate and an AMVP candidate may also beapplied to the derivation and addition of the other candidate.Repetitive descriptions will be omitted here.

Derivation of Inter-Prediction Information of Target Block UsingSub-Block

When deriving inter-prediction information of a target block, theprocessing unit may use inter-prediction information of a sub-block ofthe target block. In other words, the processing unit may useinter-prediction information corresponding to the unit of a sub-blockwhen deriving the inter-prediction information of the target block.

The processing unit may split the target block into multiple sub-blocks,and may derive inter-prediction information of each of the multiplesub-blocks. For example, the processing unit may split the target blockinto N sub-blocks, and may derive N pieces of inter-predictioninformation for the N sub-blocks. N may be a positive integer.

FIG. 27 illustrates sub-blocks of a temporal neighbor block andsub-blocks of a target block according to an example.

When inter-prediction information of a temporal neighbor block isavailable, the processing unit may partition the temporal neighbor blockinto multiple sub-blocks, and may derive pieces of inter-predictioninformation of multiple sub-blocks of the target block using pieces ofinter-prediction information of the multiple sub-blocks of the temporalneighbor block.

The processing unit may derive the pieces of inter-predictioninformation of the sub-blocks of the target block using the pieces ofinter-prediction information of the sub-blocks of the temporal neighborblock. Here, the location of a sub-block of the target block within thetarget block and the location of a sub-block of the temporal neighborblock within the temporal neighbor block may be identical to each other.

For example, the processing unit may partition temporal neighbor blockN, illustrated in FIG. 16, into 4×4 temporal sub-blocks, and may derivepieces of inter-prediction information of 4×4 sub-blocks of the targetblock using the inter-prediction information of each temporal sub-block.

For example, the processing unit may partition temporal neighbor blockN, illustrated in FIG. 16, into 2N×N temporal sub-blocks, and may derivepieces of inter-prediction information of 2N×N sub-blocks of the targetblock using the inter-prediction information of each temporal sub-block.

FIG. 28 illustrates spatial neighbor blocks of a target block andsub-blocks of the target block according to an example.

In FIG. 28, sub-blocks are indicated by capital letters “A” to “P”, andspatial neighbor blocks are indicated by small letters “a” to “h”,

The processing unit may split the target block into multiple sub-blocks,and may derive pieces of inter-prediction information of sub-blocks ofthe target block using pieces of inter-prediction information of spatialneighbor blocks for the sub-blocks of the target block.

Here, the spatial neighbor blocks for the sub-blocks of the target blockmay include 1) an additional sub-block that is adjacent to thecorresponding sub-block of the target block and 2) a block that isadjacent to the corresponding sub-block of the target block and is alsoa spatial neighbor block of the target block. Further, the spatialneighbor block may be a block on which encoding and/or decoding areperformed before the corresponding sub-block is encoded and/or decoded.

The processing unit may derive inter-prediction information of thesub-block using pieces of inter-prediction information of the spatialneighbor blocks of the sub-block. The processing unit may derive theinter-prediction information of the sub-block using pieces ofinter-prediction information of multiple spatial neighbor blocks of thesub-block. For example, the inter-prediction information of thesub-block may be the average of the pieces of inter-predictioninformation of the multiple spatial neighbor blocks of the sub-block.

For example, the processing unit may derive inter-prediction informationof sub-block A using 1) inter-prediction information of spatial neighborblock d, 2) inter-prediction information of spatial neighbor block e, or3) the average of pieces of inter-prediction information of spatialneighbor block d and spatial neighbor block e.

For example, the processing unit may derive inter-prediction informationof sub-block K using the average of pieces of inter-predictioninformation of one or more of block J, block F, block G, and block H,which are spatial neighbor blocks of sub-block K.

When deriving the inter-prediction information of the sub-block of thetarget block, the processing unit may simultaneously use a temporalneighbor block for the sub-block of the target block and a spatialneighbor block for the sub-block of the target block.

Derivation of Inter-Prediction Information Using Bilateral Matching

FIG. 29 illustrates the derivation of inter-prediction information usingbilateral matching according to an example.

The processing unit may derive inter-prediction information usingbilateral matching.

When performing bilateral matching, the processing unit may configure aninitial motion vector candidate list for a target block, and may use atleast one of one or more initial motion vector candidates, included inthe configured initial motion vector candidate list, as an initialmotion vector.

For example, the processing unit may use an AMVP mode so as to configurethe initial motion vector candidate list for the target block. AMVPcandidates in the AMVP candidate list in the AMVP mode may be the one ormore initial motion vector candidates in the initial motion vectorcandidate list. The processing unit may add the AMVP candidates includedin the AMVP candidate list to the initial motion vector candidate list.

For example, the processing unit may use a merge mode so as to configurethe initial motion vector candidate list for the target block. Mergecandidates in the merge candidate list in the merge mode may be the oneor more initial motion vector candidates in the initial motion vectorcandidate list. The processing unit may add the merge candidates in themerge mode to the initial motion vector candidate list.

For example, the processing unit may configure a Frame RateUp-Conversion (FRUC) unidirectional motion vector for the target blockas the initial motion vector candidate list. The processing unit may addthe FRUC unidirectional motion vector for the target block to theinitial motion vector candidate list.

For example, the processing unit may configure the motion vector of theneighbor block of the target block as the initial motion vectorcandidate list. The processing unit may add the motion vector of theneighbor block of the target block to the initial motion vectorcandidate list.

For example, the processing unit may configure combinations of theabove-described motion vectors as the initial motion vector candidatelist. The number of combinations of motion vectors may be N or more. Nmay be a positive integer. The processing unit may add the combinationsof the above-described motion vectors to the initial motion vectorcandidate list.

For example, the processing unit may use a motion vector for at leastone of the direction of reference picture list L0 and the direction ofreference picture list L1 upon configuring the initial motion vectorlist. The processing unit may add the motion vector for at least one ofthe direction of reference picture list L0 and the direction ofreference picture list L1 to the initial motion vector list.

The processing unit may derive an initial motion vector for the targetblock when performing bilateral matching. The processing unit may derivethe initial motion vector using the initial motion vector list.

When performing bilateral matching, the processing unit may derive abidirectional motion vector that allows an initial motion vectorindication block and the opposite block to best match each other usingthe initial motion vector list.

The initial motion vector indication block may be a block indicated bythe initial motion vector. The opposite block may be a block present onthe same trajectory as the initial motion vector indication block in adirection opposite that of the initial motion vector indication block.In other words, the direction of the initial motion vector indicationblock and the direction of the opposite block may be opposite eachother, and the trajectory of the initial motion vector indication blockand the trajectory of the opposite block may be identical to each other.

For example, as illustrated in FIG. 29, the processing unit may performbilateral matching on a target block 2911 in a target picture 2910. Whena motion vector present in the initial motion vector list is MV0 inreference picture Reference0 2920, the processing unit may derive motionvector MV1 1) which is present in reference picture Reference1 2930present in a direction opposite that of MV0, 2) which is present on thesame trajectory as the MV0, and 3) which indicates a block 2931 bestmatching a block 2921 indicated by the MV0.

In other words, when the processing unit derives the motion vector MV0using the initial motion vector for the target block and determinesmotion vector MV depending on the MV0, 1) the direction of the MV1 maybe opposite that of the MV0, and the motion trajectory of the MV1 may beidentical to that of the MV0.

The processing unit may improve the initial motion vector.

For example, the processing unit may search for blocks neighboring theblock indicated by the derived MV0, and may also search for blocksneighboring the block indicated by the derived MV1. The processing unitmay improve the initial motion vector so that the best-matching blocksare indicated among the blocks neighboring the block indicated by theMV0 and the blocks neighboring the block indicated by the MV1.

When performing bilateral matching, the processing unit may deriveinter-prediction information on a sub-block basis. The inter-predictioninformation may include motion information and/or a motion vector.

When deriving the motion information on a sub-block basis, theprocessing unit may use the above-described scheme for deriving aninitial motion vector for a block to derive an initial motion vector forthe sub-block.

When performing bilateral matching, the processing unit may define thedegree of matching between blocks. That is, the processing unit may useone of specific defined schemes upon determining the degree of matchingbetween blocks.

For example, the processing unit may determine that, when the Sum ofAbsolute Differences (SAD) between two blocks is the smallest, the twoblocks best match each other. That is, the processing unit may determinethat, as the SAD between two blocks is smaller, the two blocks bettermatch each other.

For example, the processing unit may determine that, when the Sum ofAbsolute Transformed Differences (SATD) between two blocks is thesmallest, the two blocks best match each other. That is, the processingunit may determine that, as the SATD between two blocks is smaller, thetwo blocks better match each other.

Derivation of Inter-Prediction Information Using Template Matching

FIG. 30 illustrates the derivation of inter-prediction information usinga template-matching mode according to an example.

In FIG. 30, a target block 3011 in a target picture 3010 is illustrated.

The processing unit may derive inter-prediction information usingtemplate matching.

When performing template matching, the processing unit may use aneighbor block of a target block as a template. The size and location ofthe template may be set based on a predefined scheme.

For example, the processing unit may use a neighbor block 3013 adjacentto the top of the target block 3011 as the template.

For example, the processing unit may use a neighbor block 3012 adjacentto the left of the target block 3011 as the template.

For example, the processing unit may use the neighbor block 3013adjacent to the top of the target block 3011 or the neighbor block 3012adjacent to the left thereof as the template.

In an embodiment, when performing template matching, the processing unitmay search a reference picture for a block using the template. In FIG.30, “reference 0 (3020)” may be the reference picture.

When performing template matching, the processing unit may deriveinter-prediction information using the template.

The processing unit may search the reference picture for a blockcorresponding to the template. The shape and size of the blockcorresponding to the template may be identical to those of the template.The block corresponding to the template may be the block best matchingthe template in the reference picture.

The processing unit may derive a motion vector indicating the blockcorresponding to the template. In other words, the processing unit mayderive a motion vector indicating the block best matching the templatein the reference picture.

For example, in FIG. 30, a block 3022 corresponding to the template,found for the neighbor block 3013 adjacent to the top of the targetblock, and a block 3021 corresponding to the template, found for theneighbor block 3012 adjacent to the left of the target block, aredepicted.

The processing unit may derive the motion vector of the target blockusing the motion vector of the block corresponding to the template. Theprocessing unit may set the motion vector of the block corresponding tothe template as the motion vector of the target block.

Here, the direction of the reference picture in which the block is foundand the direction of the reference picture indicated by the motionvector of the target block may be opposite each other.

The processing unit may improve the motion vector. For example, theprocessing unit may search for blocks neighboring the block indicated bythe current template and the derived motion vector, and may improve themotion vector so that the motion vector indicates the block bestmatching the template, among the found neighbor blocks. In other words,the improved motion vector may be a motion vector for the block thatbest matches the template, among the blocks neighboring the blockindicated by the derived motion vector.

When performing template matching, the processing unit may deriveinter-prediction information on a sub-block basis. The inter-predictioninformation may include motion information and a motion vector.

When deriving the motion information on a sub-block basis, theprocessing unit may use the above-described scheme for deriving a motionvector for a block to derive a motion vector for the sub-block.

When performing template matching, the processing unit may define thedegree of matching between blocks. That is, the processing unit may useone of specific defined schemes upon determining the degree of matchingbetween blocks.

For example, the processing unit may determine that, when the SADbetween two blocks is the smallest, the two blocks best match eachother. That is, the processing unit may determine that, as the SADbetween two blocks is smaller, the two blocks better match each other.

For example, the processing unit may determine that, when the SAIDbetween two blocks is the smallest, the two blocks best match eachother. That is, the processing unit may determine that, as the SAIDbetween two blocks is smaller, the two blocks better match each other.

Motion Compensation and Motion Correction for Inter Prediction

In inter prediction for a target block, the processing unit may performinter prediction using at least one of motion compensation, IC, OBMC,BIO, affine space motion prediction and motion compensation, and motionvector correction in the decoding apparatus 1300.

The processing unit may perform motion compensation to perform interprediction for a target block.

The processing unit may generate a prediction block for the target blockusing the derived inter-prediction information. Motion compensation maybe unidirectional motion compensation or bidirectional motioncompensation.

In an example, the processing unit may perform motion compensation usinga block in one picture present in one reference picture list L0.

In an example, the processing unit may perform motion compensation bycombining multiple blocks in one picture present in one referencepicture list L0.

In an example, the processing unit may perform motion compensation bycombining multiple blocks in multiple pictures present in one referencepicture list L0.

In an example, the processing unit may perform motion compensation bycombining one block in one picture present in reference picture list L0with one block in one picture present in reference picture list L1.

In an example, the processing unit may perform motion compensation bycombining multiple blocks in one picture present in reference picturelist L0 with multiple blocks in one picture present in reference picturelist L1.

In an example, the processing unit may perform motion compensation bycombining multiple blocks in multiple pictures present in referencepicture list L0 with multiple blocks in multiple pictures present inreference picture list L1.

The processing unit may perform Illumination Compensation (IC) toperform inter prediction for the target block.

When performing motion compensation, the processing unit may compensatefor lightness variation and/or illumination variation between areference picture including a reference block that is used for motioncompensation and a target picture including a target block.

For example, the processing unit may approximate variation between aneighbor sample of the target block and a neighbor sample of thereference block to N or more linear models, and may perform illuminationcompensation by applying the linear models to a motion-compensatedblock. N may be a positive integer.

FIG. 31 illustrates the application of OBMC according to an example.

The processing unit may perform OBMC to perform inter prediction for atarget block.

The processing unit may generate a prediction block by combining a firstblock with a second block. The first block may be a block generated viacompensation that uses inter-prediction information of a target block.The second block may be one or more blocks generated via compensationthat uses one or more pieces of inter-prediction information of one ormore neighbor blocks adjacent to the target block. Here, the one or moreneighbor blocks adjacent to the target block may include a left neighborblock adjacent to the left of the target block, a right neighbor blockadjacent to the right of the target block, an above neighbor blockadjacent to the top of the target block, and a below neighbor blockadjacent to the bottom of the target block.

The processing unit may perform OBMC on each sub-block of the targetblock.

The processing unit may generate a prediction block by combining a firstblock with a second block. The first block may be a block generated viacompensation that uses inter-prediction information of the sub-block ofthe target block. The second block may indicate one or more blocksgenerated via compensation that uses one or more pieces ofinter-prediction information of one or more neighbor sub-blocks adjacentto the sub-block of the target block. The inter-prediction informationmay include a motion vector. Here, the one or more neighbor sub-blocksadjacent to the corresponding sub-block of the target block may includea left neighbor sub-block adjacent to the left of the sub-block of thetarget block, a right neighbor sub-block adjacent to the right of thesub-block of the target block, an above neighbor sub-block adjacent tothe top of the sub-block of the target block, and a below neighborsub-block adjacent to the bottom of the sub-block of the target block.

The processing unit may perform OBMC only on a specific sub-block, amongthe sub-blocks of the target block.

For example, the processing unit may perform OBMC only on a sub-blockadjacent to the internal boundary of the target block.

In an example, the processing unit may perform OBMC on all sub-blocks ofthe target block.

For example, the processing unit may perform OBMC only on sub-blocksadjacent to the internal left boundary of the target block.

In an example, the processing unit may perform OBMC only on sub-blocksadjacent to the internal right boundary of the target block.

In an example, the processing unit may perform OBMC only on sub-blocksadjacent to the internal upper boundary of the target block.

In an example, the processing unit may perform OBMC only on sub-blocksadjacent to the internal lower boundary of the target block.

In FIG. 31, an example is illustrated in which a CU, which is the targetblock, is split into PU1 and PU2, OBMC is applied to 1) sub-blocksadjacent to the upper boundary, 2) sub-blocks adjacent to the leftboundary, and 3) sub-blocks adjacent to the boundary between the PUs,among the sub-blocks of the CU.

FIG. 32 illustrates sub-PUs in an ATMVP mode according to an example.

A target block may be split into multiple sub-blocks. The target blockmay be a target CU, and the sub-blocks may be sub-PUs. The processingunit may perform OBMC on all sub-blocks of the target CU.

The processing unit may generate a prediction block by combining a firstblock with a second block. The first block may be a block generated viacompensation that uses inter-prediction information of each sub-block ofthe target block. The second block may be a block generated viacompensation that uses pieces of inter-prediction information of theneighbor sub-blocks adjacent to the sub-block of the target block. Theinter-prediction information may be a motion vector. Here, the neighborsub-blocks adjacent to the corresponding sub-block of the target blockmay include a left neighbor sub-block adjacent to the left of thesub-block of the target block, a right neighbor sub-block adjacent tothe right of the sub-block of the target block, an above neighborsub-block adjacent to the top of the sub-block of the target block, anda below neighbor sub-block adjacent to the bottom of the sub-block ofthe target block.

The processing unit may perform affine space motion prediction andcompensation to perform inter prediction for the target block.

In an example, the processing unit may generate motion vectors forrespective pixels in the target block by applying an affinetransformation equation to a first motion vector at the above-leftlocation of the target block and to a second motion vector at theabove-right location of the target block, and may perform motioncompensation using the generated motion vectors.

In an example, the processing unit may generate motion vectors forrespective sub-blocks in the target block by applying an affinetransformation equation to a first motion vector at the above-leftlocation of the target block and to a second motion vector at theabove-right location of the target block, and may perform motioncompensation using the generated motion vectors.

In order to provide the first motion vector and the second motionvector, at least one of the following schemes 1) to 3) may be used.

1) The first motion vector and the second motion vector may betransmitted from the encoding apparatus 1200 to the decoding apparatus1300 (through a bitstream).

2) For each of the first motion vector and the second motion vector, thedifference between the corresponding motion vector and a neighbor motionvector thereof may be transmitted from the encoding apparatus 1200 tothe decoding apparatus 1300.

3) The first motion vector and the second motion vector may be derivedusing the affine motion vector of the neighbor block of the targetblock, without being transmitted.

The processing unit may perform BIO to perform inter prediction for atarget block.

The processing unit may derive the motion vector of the target blockusing an optical flow that uses a unidirectional block.

The processing unit may derive the motion vector of the target blockusing a bidirectional optical flow that uses blocks present in a pictureprevious to the target picture in a display sequence and blocks presentin a picture subsequent to the target picture. Here, the blocks presentin the picture previous to the target picture and blocks present in thepicture subsequent to the target picture may be blocks that haveopposite motions and are similar to the target block.

The processing unit may perform motion vector correction on the decodingapparatus 1300 to perform inter prediction for the target block. Theprocessing unit may perform correction on the motion vector of thetarget block using the motion vector that is transmitted to the decodingapparatus 1300.

FIG. 33 is a flowchart illustrating a target block prediction method anda bitstream generation method according to an embodiment.

The target block prediction method and the bitstream generation methodaccording to the present embodiment may be performed by an encodingapparatus 1200. The embodiment may be a part of a target block encodingmethod or a video encoding method.

At step 3310, the processing unit 1210 may derive inter-predictioninformation. Step 3310 may correspond to step 1410, described above withreference to FIG. 14.

At step 3320, the processing unit 1210 may perform inter prediction thatuses the derived inter-prediction information, Step 3320 may correspondto step 1420, described above with reference to FIG. 14.

At step 3330, the processing unit 1210 may generate a bitstream.

The bitstream may include information about an encoded target block. Forexample, the information about the encoded target block may includetransformed and quantized coefficients of the target block.

The bitstream may include information used to derive theinter-prediction information and information used for inter prediction.

In an example, the bitstream may include an indicator indicating amethod for deriving the inter-prediction information.

For example, the bitstream may include an index indicating one ofcandidates present in the list of the encoding apparatus 1200 or thedecoding apparatus 1300.

The processing unit 1210 may perform entropy encoding on the informationused to derive the inter-prediction information and on the informationused for inter prediction, and may generate a bitstream including piecesof entropy-encoded information.

The processing unit 1210 may store the generated bitstream in thestorage 1340. Alternatively, the communication unit 1220 may transmitthe bitstream to the decoding apparatus 1300.

FIG. 34 is a flowchart illustrating a target block prediction methodusing a bitstream according to an embodiment.

The target block prediction method using a bitstream according to thepresent embodiment may be performed by the decoding apparatus 1300. Theembodiment may be a part of a target block decoding method or a videodecoding method.

At step 3410, a communication unit 1320 may acquire a bitstream. Thecommunication unit 1320 may receive the bitstream from the encodingapparatus 1200.

The bitstream may include information about an encoded target block. Forexample, the information about the encoded target block may includetransformed and quantized coefficients of the target block.

The bitstream may include information used to derive inter-predictioninformation and information used for inter prediction.

For example, the bitstream may include an indicator indicating a methodfor deriving the inter-prediction information.

For example, the bitstream may include an index indicating one ofcandidates present in the list of each of the encoding apparatus 1200and the decoding apparatus 1300.

The processing unit 1310 may store the acquired bitstream in the storage1240.

The processing unit 1310 may acquire information used to deriveinter-prediction information and information used for inter predictionby performing entropy decoding on pieces of entropy-encoded informationin the bitstream.

At step 3420, the processing unit 1310 may derive inter-predictioninformation. Step 3420 may correspond to step 1410, described above withreference to FIG. 14.

At step 3430, the processing unit 1310 may perform inter prediction thatuses the derived inter-prediction information. Step 3430 may correspondto step 1420 described above with reference to FIG. 14.

In the above-described embodiments, although the methods have beendescribed based on flowcharts as a series of steps or units, the presentdisclosure is not limited to the sequence of the steps and some stepsmay be performed in a sequence different from that of the describedsteps or simultaneously with other steps. Further, those skilled in theart will understand that the steps shown in the flowchart are notexclusive and may further include other steps, or that one or more stepsin the flowchart may be deleted without departing from the scope of thedisclosure.

The above-described embodiments according to the present disclosure maybe implemented as a program that can be executed by various computermeans and may be recorded on a computer-readable storage medium. Thecomputer-readable storage medium may include program instructions, datafiles, and data structures, either solely or in combination. Programinstructions recorded on the storage medium may have been speciallydesigned and configured for the present disclosure, or may be known toor available to those who have ordinary knowledge in the field ofcomputer software. Examples of the computer-readable storage mediuminclude all types of hardware devices specially configured to record andexecute program instructions, such as magnetic media, such as a harddisk, a floppy disk, and magnetic tape, optical media, such as compactdisk (CD)-ROM and a digital versatile disk (DVD), magneto-optical media,such as a floptical disk, ROM, RAM, and flash memory. Examples of theprogram instructions include machine code, such as code created by acompiler, and high-level language code executable by a computer using aninterpreter. The hardware devices may be configured to operate as one ormore software modules in order to perform the operation of the presentdisclosure, and vice versa.

As described above, although the present disclosure has been describedbased on specific details such as detailed components and a limitednumber of embodiments and drawings, those are merely provided for easyunderstanding of the entire disclosure, the present disclosure is notlimited to those embodiments, and those skilled in the art will practicevarious changes and modifications from the above description.

Accordingly, it should be noted that the spirit of the presentembodiments is not limited to the above-described embodiments, and theaccompanying claims and equivalents and modifications thereof fallwithin the scope of the present disclosure.

The invention claimed is:
 1. A video decoding method, comprising:deriving inter prediction information for a target block; and performinga prediction for the target block using the inter predictioninformation, wherein a list comprising a plurality of candidates isconfigured for the target block, the prediction is performed using thelist, the plurality of the candidates are generated by adding predictioninformation of a plurality of neighbor blocks which are adjacent to thetarget block to the list according to a specific order, according to thespecific order, prediction information of an above neighbor block isadded to the list first, prediction information of a left neighbor blockis added to the list second, the above neighbor block is a right-mostblock among blocks which are adjacent to an upper side of the targetblock, and the left neighbor block is a lower-most block among blockswhich are adjacent to a left side of the target block.
 2. The videodecoding method of claim 1, wherein one candidate of the list isgenerated based on prediction information of a plurality of neighborblocks which are adjacent to the target block.
 3. The video decodingmethod of claim 2, wherein the one candidate is an average of twoprediction information of two neighbor blocks.
 4. The video decodingmethod of claim 2, wherein the one candidate is generated based onprediction information of three neighbor blocks.
 5. The video decodingmethod of claim 1, wherein the inter prediction information comprises amotion vector, and the motion vector is generated by a refinement for aninitial motion vector.
 6. The video decoding method of claim 5, whereinthe refinement is performed using a Sum of Absolute Differences (SAD)between two reference blocks.
 7. A video encoding method, comprising:deriving inter prediction information for a target block; and generatingan indicator indicating a method to derive the inter predictioninformation, a list comprising a plurality of candidates is configuredfor the target block, and a prediction is performed using the list for adecoding for the target block using the indicator, the plurality of thecandidates are generated by adding prediction information of a pluralityof neighbor blocks which are adjacent to the target block to the listaccording to a specific order, according to the specific order,prediction information of an above neighbor block is added to the listfirst, prediction information of a left neighbor block is added to thelist second, the above neighbor block is a right-most block among blockswhich are adjacent to an upper side of the target block, and the leftneighbor block is a lower-most block among blocks which are adjacent toa left side of the target block.
 8. The video encoding method of claim7, wherein one candidate of the list is generated based on predictioninformation of a plurality of neighbor blocks which are adjacent to thetarget block.
 9. The video encoding method of claim 8, wherein the onecandidate is an average of two prediction information of two neighborblocks.
 10. The video encoding method of claim 8, wherein the onecandidate is generated based on prediction information of three neighborblocks.
 11. The video encoding method of claim 7, wherein a predictionis performed using the inter prediction information for a decoding forthe target block using the indicator, the inter prediction informationcomprises a motion vector, and the motion vector is generated by arefinement for an initial motion vector.
 12. The video encoding methodof claim 11, wherein the refinement is performed using a Sum of AbsoluteDifferences (SAD) between two reference blocks.
 13. A computer-readablemedium storing a bitstream generated by the video encoding method ofclaim
 7. 14. A computer-readable medium storing a bitstream, thebitstream comprising: encoded information for a target block; wherein adecoding for the target block is performed using the encodedinformation, inter prediction information for the target block isderived, a prediction for the target block is performed using the interprediction information, a list comprising a plurality of candidates isconfigured for the target block, the prediction is performed using thelist, the plurality of the candidates are generated by adding predictioninformation of a plurality of neighbor blocks which are adjacent to thetarget block to the list according to a specific order, according to thespecific order, prediction information of an above neighbor block isadded to the list first, prediction information of a left neighbor blockis added to the list second, the above neighbor block is a right-mostblock among blocks which are adjacent to an upper side of the targetblock, and the left neighbor block is a lower-most block among blockswhich are adjacent to a left side of the target block.